Development of emergent literacy and early reading skills in preschool

Copyright 2000 by the American Psychological Association, Inc.
0012-1649/00/S5.00 DOI: 10.1037//OOI2-1649.36.5.596

Developmental Psychology
2000, Vol. 36, No. 5, 596-613

Development of Emergent Literacy and Early Reading Skills in Preschool
Children: Evidence From a Latent-Variable Longitudinal Study
Christopher J. Lonigan, Stephen R. Burgess, and Jason L. Anthony
Florida State University
Although research has identified oral language, print knowledge, and phonological sensitivity as
important emergent literacy skills for the development of reading, few studies have examined the
relations between these aspects of emergent literacy or between these skills during preschool and during
later reading. This study examined the joint and unique predictive significance of emergent literacy skills
for both later emergent literacy skills and reading in two samples of preschoolers. Ninety-six children
(mean age = 41 months, SD = 9.41) were followed from early to late preschool, and 97 children (mean
age = 60 months, SD = 5.41) were followed from late preschool to kindergarten or first grade. Structural
equation modeling revealed significant developmental continuity of these skills, particularly for letter
knowledge and phonological sensitivity from late preschool to early grade school, both of which were the
only unique predictors of decoding.

in three children experience significant difficulties in learning to
read (Adams, 1990). There is strong continuity between the skills
with which children enter school and their later academic performance. Those children who do experience early difficulties in
learning to read are likely to continue to experience reading
problems throughout the school years (Baydar, Brooks-Gunn, &
Furstenberg, 1993; Felton, 1998; Stevenson & Newman, 1986;
Tramontana, Hooper, & Selzer, 1988) and into adulthood (Bruck,
1998). For instance, Juel (1988) reported that the probability that
children would remain poor readers at the end of the fourth grade
if they were poor readers at the end of the first grade was .88.
Children who enter school with limited reading-related skills are at
high risk of qualifying for special education services. In fact, the
majority of school-age children referred for special education
evaluation are referred because of unsatisfactory progress in reading (Lentz, 1988).

Reading skills provide a crucial piece of the foundation for
children's academic success. Children who read early and well
experience more print exposure and consequent growth in numerous knowledge domains (Cunningham & Stanovich, 1997; Echols,
West, Stanovich, & Zehr, 1996; Morrison, Smith, & DowEhrensberger, 1995). In contrast, children who lag behind in their
reading skills receive less practice in reading than other children
do (Allington, 1984), miss opportunities to develop reading comprehension strategies (Brown, Palincsar, & Purcell, 1986), often
encounter reading material that is too advanced for their skills
(Allington, 1984), and may acquire negative attitudes about reading itself (Oka & Paris, 1986). Such processes may lead to what
Stanovich (e.g., 1986) termed a Matthew effect, in which poor
reading skills impede learning in other academic areas (Chall,
Jacobs, & Baldwin, 1990), which increasingly depend on reading
across the school years.
Although the development of skilled reading occurs without
significant problems for the majority of children, an estimated one

Whereas more traditional approaches to the study of reading
often take as their starting point children's entry into the formal
school environment, an emergent literacy approach conceptualizes
the acquisition of literacy as a developmental continuum with its
origins early in the life of a child, rather than as an all-or-none
phenomenon that begins when children start school. An emergent
literacy approach departs from other perspectives on reading acquisition in suggesting that there is no clear demarcation between
reading and prereading. Emergent literacy consists of the skills,
knowledge, and attitudes that are presumed to be developmental
precursors to conventional forms of reading and writing (Sulzby &
Teale, 1991; Teale & Sulzby, 1986; Whitehurst & Lonigan, 1998),
and thus it suggests that significant sources of individual differences in children's later reading skills are present prior to school
entry. Previous research has identified a number of potentially
important components of emergent literacy. Whitehurst and Lonigan (1998) recently outlined different components of emergent
literacy skills and identified three factors that appear to be associated with preschool children's later word-decoding abilities: oral
language, phonological processing abilities, and print knowledge.

Christopher J. Lonigan, Stephen R. Burgess, and Jason L. Anthony,
Department of Psychology, Florida State University.
Stephen R. Burgess is now at the Department of Psychology, Southwestern Oklahoma State University.
Preparation of this article was supported, in part, by grants from the
National Institute of Child Health and Human Development (HD36067,
HD36509) and the Administration for Children and Families (90-YF0023); the views expressed herein are the authors' and have not been
cleared by the grantors.
We wish to acknowledge the contributions of the child-care centers, the
directors, and the personnel who assisted with this project as well as the
children and parents who made it possible. We thank Sarah Dyer, Brenlee
Bloomfield, Crystal Carr, Tracy Ferguson, Kimberly Ingram, Danielle
Karlau, Nikki Sutton, Emily Shock, and other students at Florida State
University for their assistance with data collection.
Correspondence concerning this article should be addressed to Christopher J. Lonigan, Department of Psychology, Florida State University,
Tallahassee Florida 32306-1270. Electronic mail may be sent to
lonigan@psy.fsu.edu.
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EMERGENT LITERACY AND EARLY READING
Reading is a process of translating visual codes into meaningful
language. In the earliest stages, reading in an alphabetic system
involves decoding letters into corresponding sounds and linking
those sounds to single words. A substantial body of research has
demonstrated positive correlations and longitudinal continuity between individual differences in oral language skills and later
differences in reading (e.g., Bishop & Adams, 1990; Butler,
Marsh, Sheppard, & Sheppard, 1985; Pikulski & Tobin, 1989;
Scarborough. 1989; Share, Jorm, MacLean, & Mathews, 1984).
Whereas the connection between oral language and reading is clear
for reading comprehension (e.g., Snow, Barnes, Chandler, Hernphill, & Goodman, 1991), some studies indicate that vocabulary
skills also have a significant impact on decoding skills very early
in the process of learning to read (e.g., Wagner et al.. 1997).
Additionally, oral language appears to be related to a second
emergent literacy skill, phonological sensitivity, as defined below.
Studies of both preschool (e.g., Burgess & Lonigan, 1998; Chaney,
1992; Lonigan, Burgess, Anthony, & Barker, 1998) and early
elementary school children (e.g., Bowey, 1994; Wagner, Torgesen,
Laughon, Simmons, & Rashotte, 1993; Wagner et al., 1997) have
demonstrated significant concurrent and longitudinal correlations
between children's vocabulary skills and their phonological
sensitivity.
Phonological sensitivity refers to sensitivity to and ability to
manipulate the sound structure of oral language. Research with a
variety of populations and using diverse methods has converged on
the finding that phonological sensitivity plays a critical and causal
role in the normal acquisition of reading (e.g., Adams, 1990; Byrne
& Fielding-Bamsley. 1991; Slanovich, 1992; Wagner & Torgesen,
1987). Children who are better at detecting and manipulating
syllables, rhymes, or phonemes are quicker to learn to read, and
this relation is present even after variability in reading skill owing
to factors such as IQ, receptive vocabulary, memory skills, and
social class is partialed out (e.g., Bryant, MacLean, Bradley, &
Crossland, 19%; Wagner & Torgesen, 1987; Wagner, Torgesen, &
Rashotte, 1994). Moreover, studies of disabled and poor readers
indicate that there is a core phonological deficit in nearly all poor
readers regardless of whether their reading abilities are consistent
or inconsistent with their general cognitive abilities (Stanovich,
1988; Stanovich & Siegel, 1994; Torgesen, 1999).
In addition to oral language and phonological sensitivity, aspects of children's print knowledge seem to be important emergent
literacy skills. For example, knowledge of the alphabet (i.e., knowing the names of letters and the sounds they represent) at entry into
school is one of the strongest single predictors of short- and
long-term success in learning to read (e.g., Adams, 1990; Stevenson & Newman, 1986). Understanding the conventions of print
(e.g., left-to-right and top-to-bottom orientation of print, the difference between pictures and print on a page; Clay, 1979a, 1979b)
and the functions of print (e.g., that the print tells a story or gives
directions; Purcell-Gates, 1996; Purcell-Gates & Dahl, 1991) also
appears to aid in the process of learning to read. For example,
Tunmer, Herriman, and Nesdale (1988) found that children's
scores on Clay's (1979a) Concepts About Print (CAP) Test at the
beginning of first grade predicted their reading comprehension and
decoding abilities at the end of second grade even after Tunmer et
al. controlled for differences in vocabulary and metalinguistic
awareness. Some emergent literacy advocates have also suggested
that children's faculty with environmental print (e.g., recognizing

597

product names from signs and logos) reflects their early print
awareness by demonstrating the ability to derive the meaning of
text within context (e.g., Goodman, 1986).
Despite some evidence for associations between emergent literacy and later reading, there have been relatively few studies
examining the relations between these multidimensional aspects of
emergent literacy or between these components during the preschool period and later reading skills. As noted above, aspects of
oral language appear to be related to phonological sensitivity.
Children's letter knowledge also appears to be associated with
some aspects of phonological sensitivity (Bowey, 1994; Stahl &
Murray, 1994) and growth in these skills (Burgess &. Lonigan,
1998; Wagner et al., 1994, 1997). Evidence from school-age
children indicates that these three components of emergent literacy
are causally related to each other and to later reading (e.g., Wagner
et al., 1997); however, how they relate to each other during the
preschool period is not known. Consequently, it is not clear
whether there are interactions between these different emergent
literacy skills or whether they are relatively independent of one
another, and thus a well-elaborated developmental model of preschool emergent literacy and its relation to conventional literacy
cannot be advanced. Moreover, basic questions concerning the
nature of preschool phonological sensitivity currently remain unanswered, as discussed below.
The majority of evidence linking phonological sensitivity in
prereaders with the development of reading has come from studies
that have assessed phonological skills at the point of school entry
but prior to formal reading instruction (e.g., Bradley & Bryant,
1983, 1985; Share et al., 1984; Stanovich, Cunningham, & Cramer, 1984; Wagner etal., 1994, 1997). Compared with research on
school-age children's phonological sensitivity, there has been significantly less systematic study of preschool children's phonological sensitivity, and many of these studies have been limited by
small sample sizes, use of only one or two measures of phonological sensitivity, and other methodological weaknesses.
In one of the more extensive studies to date, MacLean, Bryant,
and Bradley (1987) administered a rhyme detection task and a
knowledge-of-nursery-rhymes task to a group of 66 three-year-old
children. When the children were 4'/2 years old, their ability to
read 12 simple high-frequency words was assessed. Compared
with nonreaders, children who could read some of these words
scored higher on the earlier rhyme and alliteration measures.
Bryant et al. (1990) reported additional data on these children, who
completed additional rhyme and alliteration detection tasks when
they were about 4'/i years old, phoneme deletion and phoneme
tapping tasks when they averaged about 6 years of age, and reading
and spelling tests when they averaged about 6V2 years of age.
Bryant et al. found that the rhyme and alliteration detection tests
that had been administered when the children were AV2 were
correlated with the later phoneme deletion and phoneme tapping
tasks (average r = .48), and scores on these rhyme and alliteration
tasks significantly added to the prediction of reading and spelling
scores independent of mothers' educational level, child age, IQ,
receptive vocabulary, and the score on either the phoneme deletion
or phoneme tapping tasks.
Evidence suggests that there is a developmental hierarchy of
children's sensitivity to linguistic units at different levels of complexity. Children achieve syllabic sensitivity earlier than they
achieve sensitivity to phonemes, and children's sensitivity to in-

598

LONIGAN, BURGESS, AND ANTHONY

trasyllabic units (i.e., onset-rime) also precedes sensitivity to phonemes (Fox & Routh, 1975; I. Liberman, Shankweiler, Fischer, &
Carter, 1974; Lonigan et al., 1998; Treiman, 1992). However,
there is controversy concerning whether sensitivity to lower levels
of linguistic complexity (i.e., syllables, onset-rime) represents processes important for reading. Sensitivity to phonemes is often
assumed to have special status in the relation between phonological sensitivity and reading both because it is at this level that
graphemes correspond to speech sounds in reading and because
individual phonemes do not have separable physical reality (e.g.,
A. Liberman, Cooper, Shankweiler, & Studdert-Kennedy, 1967;
Morais, 1991; Muter, Hulme, Snowling, & Taylor, 1997; Nation &
Hulme, 1997; Tunmer & Rohl, 1991). Other authors have suggested that children's abilities to detect rhyme facilitate reading
through a mechanism different than sensitivity to phonemes (e.g.,
Goswami & Bryant, 1990, 1992).
Both of these views, however, assume that there is more than
one type of phonological sensitivity and that the different types
may be more or less related to reading. Most extant studies
compared the ability of different phonological sensitivity measures
(e.g., measures of rhyme vs. phonemic sensitivity) to predict
reading. In these studies, when one measure of phonological
sensitivity predicts reading better—typically defined as a significant semi-partial correlation obtained while controlling for the
other measure of phonological sensitivity—the results are taken as
supporting the crucial importance of the skill supposedly measured
by that task (e.g., phonemic sensitivity). For example, in support of
the importance of phonemic sensitivity, both Muter et al. (1997)
and Nation and Hulme (1997) reported that children's abilities to
perform a phoneme segmentation task were more strongly related
to reading and spelling than were their abilities to detect and
produce rhyme. Goswami and Bryant (1992) also reported data
consistent with separate domains of phonological sensitivity. In
their study, when they controlled for phonemic sensitivity, rhyming abilities facilitated children's abilities to make use of analogy
in reading unfamiliar words. There are several problems with this
predictive approach. First, it assumes a priori that there are different types of phonological sensitivity. Second, it ignores the fact
that the most predictive element in such studies is the overlap
between measures (i.e., the degree of shared predictive variance is
substantially larger than the degree of unique predictive variance
for a given test). Finally, these types of analyses fail to take into
account the effects of differential reliability of the measures. That
is, the more reliable of two variables measuring equally predictive
constructs (or the same construct) generally will capture the unique
predictive variance.
Prior to examining differential predictive validity, therefore, it is
important that we determine whether there is more than one type
of phonological sensitivity. Extant evidence suggests that sensitivity to onset-rimes, syllables, and phonemes represents the same
underlying ability. For example, Stahl and Murray (1994) administered to 113 kindergarten and first-grade children four different
tasks varying in linguistic complexity. Separate factor analyses of
the four tasks across linguistic complexity and of the four levels of
linguistic complexity across tasks each yielded a single-factor
solution that explained a majority of the variance in children's
performance on the measures. Using confirmatory factor analysis,
Anthony et al. (2000) found that a single factor provided the best
fit to preschool children's scores on measures of rhyme, syllable,

and phoneme sensitivity (see also Anthony & Lonigan, 2000). In
contrast to these findings, however, Hoien, Lundberg, Stanovich,
and Bjaalid (1995) reported evidence for the distinction between
sensitivity to phonemes and sensitivity to rhyme and syllables.
They found separate factors for phonemic sensitivity, syllabic
sensitivity, and rhyme sensitivity in 6- and 8-year-old Norwegian
children, and scores on all three factors independently predicted
reading abilities for the older group of children. However, it is
difficult to interpret the results of Hoein et al. because only one
task defined the Rhyme Sensitivity and Syllabic Sensitivity
factors.
Several predictive studies also support a unitary view of phonological sensitivity. For example, Lonigan et al. (1998) demonstrated that preschool children's performance on tasks measuring phonological sensitivity at the syllable, onset-rime, and phoneme levels was associated with measures of letter knowledge and
decoding. Similarly, studies of school-age children by Wagner and
colleagues (Wagner et al., 1993, 1994, 1997) found that a latent
variable defined by rhyme, syllable-level, and phoneme-level tasks
was associated strongly, concurrently, and longitudinally with
children's reading skills. These findings indicate that the variance
common to phonological sensitivity tasks measuring different levels of linguistic complexity represents the predictive aspect of the
phonological sensitivity construct. However, the majority of predictive studies have involved either school-age children or relatively small samples. Consequently, little is known about the
nature and predictive importance of preschool children's developing phonological sensitivity.
Questions concerning the nature of preschool phonological sensitivity (i.e., whether it is a unitary or a multidimensional construct), the independence of phonological sensitivity, oral language, and print knowledge, as well as the significance of these
three components of emergent literacy for later reading are important because studies demonstrate that there are highly stable individual differences in these abilities from kindergarten forward
(Wagner et al., 1994, 1997). Such findings suggest that the preschool period is an important source of development in skills
associated with later reading. Our goals in this study were to
examine the nature of preschool emergent literacy as well as the
joint and unique predictive significance of preschool emergent
literacy skills for later reading. We examined the development of
emergent literacy and early reading longitudinally in two samples
of preschool children who overlapped in age at different assessment points and in the measures they completed. We used structural equation modeling to address questions about the nature of
preschool phonological sensitivity, the independence of different
emergent literacy skills, and the developmental significance of
these skills across time from the early preschool period to kindergarten and first grade.

Method
Participants
Data from two groups of preschool-age children, recruited through 13
different preschools and child-care centers serving middle- to upper-

income families, were used in this study.1 One group of children consisted
of 96 younger preschoolers who completed follow-up testing (i.e., Time 2)
approximately 18 months after their initial (i.e., Time 1) assessments.
These children ranged in age from 25 to 61 months (M = 41.02 months,
SD = 9.41) at Time 1. The majority of the younger group of children were
White (89.6%), and 56.3% were girls. The second group of children
consisted of 97 older preschoolers who completed follow-up tests (i.e.,
Time 2) approximately 12 months after their initial (i.e., Time 1) testing.
This group of children ranged in age from 48 to 64 months (M = 60.04
months, SD = 5.41) at Time 1. Most of the older group of children were
White (96.9%), and 52.6% were girls. Only children who had completed all
measures at both Time 1 and Time 2 were included in these samples. An
additional 58 children (18 from the older sample) who had incomplete data
on measures at Time 1 or Time 2 either because they refused continued
participation or because they could not be located for the Time 2 testing
were excluded from the results reported in this study. With the exception
that excluded children in the younger sample scored lower on the rhyme
oddity task (p = .04), excluded children did not differ from included
children on any measure.
These two samples of children originally were recruited for separate but
related research projects, and there was substantial overlap in the primary
measures administered in each project. The grouping used in this study
maintained the original division between samples because of the different
follow-up periods associated with each and the commonality of measures
administered at each assessment within a sample. Information concerning
children's family and home literacy experiences obtained on a majority of
participants (85%) revealed that the samples were similar to each other on
these variables. English was the primary language spoken in the home for
all children, and fewer than three mothers or three fathers reported that
English was not their native language. Mothers and fathers of children in
both samples had completed on average 16 years of education (in both
samples over 70% of mothers and over 63% of fathers were college
graduates). Parents reported a significant number of children's books in the
home for both the younger (M = 89.47, SD = 67.5) and older (M =
137.75, SD = 92.9) samples. Children in both samples were reported to be
read to frequently at home (younger sample, M = 6.69 times per week,
SD = 3.22; older sample, M = 5.71, SD = 2.35), and shared reading had
started early for children in both the younger (M = 6.37 months,
SD = 6.18) and older (M = 7.33 months, SD = 4.48) samples.

Preschool and Child-Care Centers
Although we did not conduct formal observations of the centers, our
multiple opportunities for observation allowed us to identify salient features of their educational environments. There was significant variability
between centers in terms of materials available to the children and activity
structure. Generally, the curriculum in the centers was designed to foster
social and interpersonal skill growth and to introduce the children to a
variety of educationally relevant concepts such as letters, numbers, and
storybooks. We never observed any explicit attempts to teach the children
to read in any center. Some of the centers had at least some letter
knowledge instruction, but most of this was informal. A number of directors commented that they discouraged explicit teaching. The centers had
similar daily activity schedules, including free play, storytime, and smallgroup arts and crafts projects. Each of the centers incorporated some
teacher-directed classroom activities (typically arts and crafts); however,
the majority of children's time was spent in self-directed activities in and
out of the classroom.

Procedures and Measures
After parents provided informed consent for their children to participate,
trained research assistants tested children individually in their centers. Test
administration for individual children was conducted over two to four

599

sessions within a 2-3-week period to ensure optimal performance on all
tasks. Children in the younger sample completed four standardized tests of
oral language, four tests of phonological sensitivity, and two tests of
nonverbal cognitive ability during Time 1 testing, and they completed four
tests of phonological sensitivity, two tests of letter knowledge, an environmental print task, and a print concepts task during Time 2 testing.
Children in the older sample completed one test of oral language, four tests
of phonological sensitivity, two tests of letter knowledge, an environmental
print task, and a print concepts task during Time 1 testing, and they
completed four tests of phonological sensitivity, two tests of letter knowledge, a print concepts task, and two text decoding tasks during Time 2
testing.
Phonological sensitivity measures. Each of the four phonological sensitivity tasks was preceded by practice trials to teach children the task (e.g.,
blending or deleting word sounds). For all tasks, corrective feedback was
given during the practice trials, but no feedback was given during the test
trials. Many items on the phonological sensitivity tasks used pictures to
reduce memory demands on the children. Except as noted below, tasks
administered at Time 1 and Time 2 and to younger and older children
included the same items. Previous analyses of these four tasks indicated
that they had moderate to high internal consistencies for 4-year-olds (as =
.47 to .96) and 5-year-olds (as = .69 to .94) but lower internal consistencies for 2- and 3-year-olds (see Lonigan et al., 1998).
A rhyme oddity detection task and an alliteration oddity detection task,
patterned after the tasks developed by MacLean et al. (1987) and using
their word lists, required children to demonstrate awareness of rhyme or
awareness of singleton word onsets. In both tasks, children were presented
with three pictured words (e.g., boat, sail, nail; car, cat, sun), which were
named by the examiner, and were asked to select the one that did not rhyme
with (or that sounded different from) or did not sound the same at the
beginning of the word as (or that sounded different at the beginning of the
word from) the other two words. Two practice trials and 11 test trials were
presented to all children.
A blending task required children to combine word elements to form a
word. Three practice items and the first eight test trials were presented both
verbally and with pictures; the remaining test trials were presented verbally
only. In both picture and nonpicture trials, the first five items required
blending single-syllable words to form compound words, and the remaining items required blending syllables or phonemes. For picture items
involving compound words, the examiner showed the child two pictures,
named them, and then asked the child what word would be produced if he
or she said them together (e.g., "What do you get when you say cow . . .
boy together?"). All practice items required the blending of compound
words, and during the practice the examiner emphasized the nature of the
task by putting the pictures together. For the Time 1 assessment of the older
sample and both Time 1 and Time 2 assessments of the younger sample,
there were 18 test trials, consisting of 10 word-blending items, 4 syllableblending items, and 4 phoneme-blending items. At the Time 2 assessment
of the older children, there were 37 test trials, consisting of all of the
Time 1 items followed by 3 additional syllable-blending items and 16
additional phoneme-blending items. These additional syllable and phoneme items were included in the older children's Time 2 assessment to
reduce the chances of children's scoring at ceiling levels. During both
assessments, testing was discontinued after a child missed 5 consecutive
trials.
An elision task required children to say a word minus a specific sound.
Two practice items and the first eight test trials were presented both

1
These children represent a subset of the children from middle-income
families included in Lonigan et al. (1998). The results reported previously
concerned age- and SES-related performance differences in phonological
sensitivity tasks from the children's initial assessment (i.e., Time 1 in the
present study).

600


verbally and with pictures; the remaining test trials were presented verbally
only. In both picture and nonpicture trials, the first four items required
deleting a single-syllable word from a compound word to form a new word.
Subsequent items in both picture and nonpicture trials required deletion of
a syllable or a phoneme from a word to form a new word. For picture items
involving compound words, the examiner showed the child two pictures,
named them (e.g., "This is a bat, and this is a man."), asked the child to say
the compound (i.e., "batman"), and then asked the child to delete part of it.
During both practice trials, which used compound words, the examiner
emphasized the nature of the task by removing the picture of the word to
be deleted. For the Time 1 assessment of the older children and both
Time 1 and Time 2 assessments of the younger children, there were 17 test
trials, consisting of 10 word-level items, 4 syllable-level items, and 3
phoneme-level items. At the Time 2 assessment of the older children, there
were 34 test trials, consisting of all of the Time 1 items followed by an
additional 17 phoneme-level items. These additional phoneme items were
included in the older children's Time 2 assessment to reduce the chances
of children's scoring at ceiling levels. During both assessments, testing was
discontinued after a child missed 5 consecutive trials.
Oral language and cognitive ability measures. At Time 1, children in
the younger sample completed four standardized tests of oral language.
Receptive vocabulary was assessed with the Peabody Picture Vocabulary
Tests—Revised (PPVT-R; Dunn & Dunn, 1981). Expressive vocabulary
was assessed with the Expressive One-Word Picture Vocabulary Test—
Revised (EOWPVT-R; Gardner, 1990). The Verbal Expression subtest of
the Illinois Test of Psycholinguistic Abilities (ITPA-VE; Kirk, McCarthy,
& Kirk, 1968) was used to assess children's descriptive use of language,
and the Grammatical Closure subtest of the Illinois Test of Psycholinguistic Abilities (ITPA-GC; Kirk et al., 1968) was used to assess children's
expressive grammar. At Time 1 for the older children, oral language was
assessed with the ITPA-GC. In addition to these oral language measures,
children in the younger sample completed the Picture Completion and
Object Assembly subtests from the Wechsler Preschool and Primary Scales
of Intelligence—Revised (Wechsler, 1989) at Time 1.
Letter knowledge measures. For the Time 2 assessment of the younger
sample and both Time 1 and Time 2 assessments of the older sample, two
tasks assessed different aspects of letter knowledge. A letter-name knowledge task required children to name all 26 uppercase letters that were
presented individually in random order on individual 3 X 5 in. index cards.
A letter-sound knowledge task required children to name the sound made
by each letter when it appeared in a word. All 26 uppercase letters were
presented individually in random order on individual 3 X 5 in. index cards.
If children responded with the letter name or a word that started with the
letter (e.g., "dog" for D), they were prompted to provide the letter sound;
however, credit for a correct response was given if children provided the
long vowel sound for vowels.
Environmental print measures. The older sample at Time 1 and the
younger sample at Time 2 completed an environmental print task. On this
task, children were shown 11 pictures of print in environmental context
(e.g., a stop sign, a Coke machine, a McDonald's sign) and were asked
what each said. Children were also shown the same print as printed text out
of context and were asked what it said.
Print concepts measure. At Time 2 for the younger sample and at both
Time 1 and Time 2 for the older sample, portions of Clay's (1979a) CAP
test (the"Sand" task) were used to assess the children's print knowledge.
Items in this test require children to demonstrate understanding of the
left-to-right and top-to-bottom direction of print in a book, the sequence
and direction in which print progresses from front to back across pages, the
difference between the covers and the pages of a book, the difference
between pictures and print on a page, and the meaning of elements of
punctuation, including spaces between words and periods at the ends of
sentences.
Word decoding measures. At Time 2, children in the older sample
completed the Word Identification subtest of the Woodcock Reading

Mastery Test—Revised (Woodcock, 1987) and a task requiring them to
decode 25 frequent words printed individually on 3 X 5 in. index cards.

Results
Descriptive Statistics and Preliminary Analyses
Separate scores for word, syllable, and phoneme items on the
blending and elision tasks were computed. Descriptive statistics
for raw scores on all variables for the younger sample at both
Time 1 and Time 2 are shown in Table 1. Descriptive statistics for
raw scores on all variables for the older sample at both Time 1 and
Time 2 are shown in Table 2. The tables also list the internal
consistency reliabilities for the eight phonological sensitivity
scores at both assessments; with a few exceptions, these reliabilities were at least moderate. Analyses of variance (ANOVAs)
revealed that the older sample scored substantially higher than the
younger sample on the phonological sensitivity measures at
Time 1 (all ps < .001). For all tasks that were the same between
Time 1 and Time 2 assessments (i.e., all phonological sensitivity
tasks for the younger sample and the letter knowledge and wordlevel phonological sensitivity tasks for the older sample), withinsubject ANOVAs revealed that there was significant growth from
Time 1 to Time 2 (all ps < .001).
Standardized scores for both samples were computed by regressing chronological age onto the raw score for each variable
within sample and time of assessment (i.e., Time 1 and Time 2) to
remove statistically the reliable variance that was due to children's
chronological age from the scores on the observed variables.
Inspection of the distribution of scores for each variable revealed
some moderate departures from normality (i.e., skew) but no
obvious outliers. Further inspection revealed that positive skew for
the younger children's Time 1 scores was due to a moderate
number of children scoring at low levels on the blending and
elision tasks, whereas negative skew for the older children's scores
was due to a moderate number of children scoring at high levels on
the word blending, word elision, and letter knowledge tasks. Although these distributions accurately reflect task difficulty for the
age ranges included in the samples, the use of nonnormal data may
attenuate relations among variables and compromise model fits;
consequently, we conducted confirmatory factor analysis (CFA)
using robust maximum-likelihood estimation, the Satorra-Bentler
scaled chi-square (S-B;^2), and adjustments to the standard errors
to account for nonnormality in model fit statistics and significance
testing (Bentler & Dudgeon, 1996).

Evaluation of Measurement Models
We conducted separate CFAs using EQS (Bentler, 1995) to
evaluate measurement models for both samples at Time 1 and
Time 2. All CFAs were conducted on covariance matrices. Prior to
evaluating the adequacy of measurement models that included all
emergent literacy tasks, we evaluated the adequacy of a one-factor
model to explain scores on the phonological sensitivity tasks at
each measurement period for both samples. In all models, task
variance for the different phonological sensitivity tasks was modeled by allowing correlated residuals between similar tasks (i.e.,
parameter estimates for covariances between error terms for the
two oddity tasks, three blending tasks, and three elision tasks were

601


Table 1
Descriptive Statistics for Younger Sample of Children at Time 1 and Time 2 Assessments
Time 1
Variable

M

SD

Age (in months)
Rhyme oddity
Alliteration oddity
Blending words
Blending syllables
Blending phonemes
Elision words
Elision syllables
Elision phonemes
PPVT-R (MA)
EOWPVT-R (MA)
ITPA-VE (MA)
ITPA-GC (MA)
WPSSI Object Assembly
WPSSI Picture Completion
Letter names
Letter sounds
Concepts About Print Test
Environmental print: pictures
Environmental print: text

41.05
4.54
3.45
2.57
0.68
0.25
1.77
0.43
0.22
42.54
42.71
48.54
45.48
12.40
10.48
—
—
—
—
—

9.36
2.00
1.81
4.47
1.35
0.62
2.77
0.95
0.70
11.60
12.90
13.09
14.87
5.31
6.77
—
—
—
—
—

Time 2
a

.30
.18
.97
.90
.52
.91
.79
.86

M

SD

a

57.56
6.93
5.55
7.30
1.51
1.31
5.73
1.95
1.12
—
—
—
—
—
—
14.51
6.84
7.26
5.22
0.97

10.09
2.52
2.66
5.88
1.34
1.48
3.83
1.59
1.20

.90
.85
.98
.89
.87
.96
.88
.85

—
—
—
—
—
10.06
8.32
3.32
2.69
2.13

Note. N = 96. All means are for raw scores unless otherwise noted. Internal consistency reliabilities (alphas)
are provided only for phonological sensitivity measures. Dashes indicate tasks not administered at an assessment
period. PPVT-R = Peabody Picture Vocabulary Test—Revised; MA = mental age score; EOWPVT-R =
Expressive One-Word Picture Vocabulary Test—Revised; ITPA-VE = Verbal Expression subscale of the
Illinois Test of Psycholinguistic Abilities; ITPA-GC = Grammatical Closure subtest of the Illinois Test of
Psycholinguistic Abilities; WPPSI = Wechsler Preschool and Primary Scales of Intelligence.

specified in the models).2 For the younger sample at Time 1,
S-B^CB, N = 96) = 13.15, p > .25, RCF1 (robust comparative
fit index) = 1.00, and Time 2, S-Bx^B.iV = 96) = 5.23,p > .25,
RCFI = 1.00, and for the older sample at Time 1, S-Bx^B, N =
97) = 17.89, p > .10, RCFI = .98, and Time 2, S - B ^ D , N =
97) = 10.78, p > .25, RCFI = 1.00, a one-factor model provided
an excellent fit to the data. Following these analyses, different
one-, two-, and three-factor measurement models that included all
emergent literacy tasks were compared in the younger and older
samples at the Time 1 and Time 2 assessments.
Younger sample. Fit indices for the different measurement
models for the younger sample of children are shown in Table 3.
For the Time 1 assessment (upper half of Table 3), the fits of
models that included different combinations of phonological sensitivity, oral language, and nonverbal IQ measures were compared.
A three-factor model with separate Phonological Sensitivity, Oral
Language, and Nonverbal IQ factors provided a significantly better
fit than all of the alternative models (all ps < .01 for chi-square
difference tests) except the model with the phonological sensitivity
and oral language measures represented by one factor. The difference (diff) between the three-factor model and this two-factor
model was only marginally significant, ^ iff <2, N = 96) = 4.09,
p = .11; however, examination of the other fit indices (Bentler &
Bonett, 1980; see Table 3) and factor loadings, which indicated
that the majority of phonological sensitivity tasks did not load
significantly on the factor, supported the superiority of the threefactor model.
For the younger sample's Time 2 assessment (see lower half of
Table 3), the fits of models that included different combinations of

phonological sensitivity, letter knowledge, and environmental
print measures were compared. These models also included the
CAP test as a separate measured variable. A three-factor model
that included different Phonological Sensitivity, Letter Knowledge, and Environmental Print factors provided a significantly
better fit than the one-factor model, XdiffC5- N - 96) = 49.34, p <
.001, a two-factor model with phonological sensitivity and letter
knowledge measures represented by a single factor, Xdiff(3, N =
96) = 42.07, p < .001, and a two-factor model with phonological
sensitivity and environmental print measures represented by a
single factor, *jjiff(3, N = 96) = 39.12, p < .001. The two-factor
model with letter knowledge and environmental print measures
represented by a single factor was not significantly different from
the three-factor model (p > .10); however, when the CAP measure
was excluded from the model, the three-factor model provided a
better fit to the data, xjiiff(2, N = 96) = 6.40, p < .05, supporting
the use of three separate factors to represent phonological sensitivity, letter knowledge, and environmental print.
Older sample. Fit indices for the different measurement models for the older sample of children are shown in Table 4. For the
Time 1 assessment (see upper half of Table 4), the fits of models
2
The structure of all measurement and longitudinal models was identical
whether or not these correlated residuals were included in the models;
however, model fits were improved when correlated residuals were included because they accounted for significant covariance between items
that was due to similar task methods (e.g., blending vs. deleting word
sounds) or other sources of systematic variance.

602

Table 2

Descriptive Statistics for Older Sample of Children at Time 1 and Time 2 Assessments
Time 1

Time 2

Variable

M

SD

a

Age (in months)
Rhyme oddity
Alliteration oddity
Blending words
Blending syllables
Blending phonemes
Elision words
Elision syllables
Elision phonemes
Letter names
Letter sounds
Environmental print: pictures
Environmental print: text
ITPA-GC (MA)
Decoding frequent words
WRM Word ID

60.04
6.49
5.46
7.73
2.70
1.78
5.59
2.13
1.14
20.02
9.09
7.63
5.73
0.97
68.64
—
—

5.41
2.75
2.64
2.95
1.39
1.40
2.37
1.43
1.06
7.37
8.91
3.32
2.17
1.91
16.22
—
—

SD

72.88
8.89
8.73
9.44
10.16
6.96
7.56
2.32
6.42
24.72
20.45
11.41
—
—

5.71
2.13
2.42
1.16
2.70
3.65
0.69
0.97
3.87
3.68
6.68
1.70
—

11.98
14.32

.71
.68
.93
.69
.67
.80
.70
.57

M

8.46
12.12

a
.71
.80
.75
.61
.90
.50
.44
.88

Note. N = 97. All means are for raw scores unless otherwise noted. Internal consistency reliabilities (alphas)
are provided only for phonological sensitivity measures. Dashes indicate tasks not administered at an assessment
period. ITPA-GC = Grammatical Closure subtest of the Illinois Test of Psycholinguistic Abilities; MA = mental
age score; WRM Word ID = Word Identification subtest of the Woodcock Reading Mastery Test—Revised.

that included different combinations of phonological sensitivity, letter knowledge, and environmental print measures were
compared. These models also included the CAP test as a separate measured variable. Both chi-square difference tests and
evaluation of the other fit indices indicated that a three-factor
model that included separate Phonological Sensitivity, Letter
Knowledge, and Environmental Print factors provided a significantly better fit than the one-factor model, ^ i f f ( 5 , N =
97) = 32.49, p < .001, a two-factor model with phonological

sensitivity and letter knowledge measures represented by a
single factor, )&i{f(3, N = 97) = 10.89, p < .05, a two-factor
model with phonological sensitivity and environmental print
measures represented by a single factor, Xdiff(3, N =
97) = 24.39, p < .001, and a two-factor model with letter
knowledge and environmental print measures represented by a
single factor, Xdiff(3, N = 97) = 18.91, p < .001, supporting the
use of three separate factors to represent phonological sensitivity, letter knowledge, and environmental print.

Table 3
Fit Indices for Measurement Models for Younger Sample at Time 1 and Time 2 Assessments
Model (and factors)

S-B*2

df

CFI

RCFI

TLI

RMSEA

AIC

.91
.94
.82
.91
.95

.85
.88
.82
.90
.92

.10
.09
.11
.08
.07

-9.57
-18.20
3.74
-29.98
-36.14

.88
.89
.90
.96
.96

.84
.84
.85
.94
.94

.11
.11
.11
.07
.07

7.44
5.25
2.51
-32.85
-32.26

Time 1 Assessment
1-factor
2-factor
2-factor
2-factor
3-factor

(PS + OL + IQ)
(PS + OL, IQ)
(PS + IQ, OL)
(PS, OL + IQ)
(PS, OL, IQ)

102.70**
89.82*
130.77***
99.43**
85.73

70
69
69
69
67

.89
.91
.86
.93
.94

Time 2 Assessment
1-factor
2-factor
2-factor
2-factor
3-factor

(PS + LK + EP)
(PS + LK, EP)
(PS + EP, LK)
(PS, LK + EP)
(PS, LK, EP)

123.05***
115.78***
112.83***
80.45*
73.71*

58
56
56
56
53

.88
.89
.90
.96
.96

Note. All models include correlated residuals between like phonological sensitivity tasks. All models of Time 2
assessment include scores on the Concepts About Print Test as a measured variable. N = 96. PS = Phonological
Sensitivity; OL = Oral Language; IQ = Nonverbal IQ; LK = Letter Knowledge; EP = Environmental Print;
S-B^2 = Satorra-Bentler chi-square; CFI = comparative fit index; RCFI = robust comparative fit index; TLI =
Tucker-Lewis index; RMSEA = root mean square error of approximation; AIC = Akaike information criterion.
*p<.05.

**p<.0l.

***/><.001.


603

Table 4
Fit Indices for Measurement Models for Older Sample at Time 1 and Time 2 Assessments
Model (and factors)

S-B*2

df

CFI

RCFI

TLI

RMSEA

AIC

.86
.91
.87
.89
.92

.82
.88
.84
.85
.90

.10
.09
.10
.09
.08

-0.34
-18.16
-4.68
-10.24
-22.76

.90
.97
.95
.95
1.00

.86
.95
.93
.92
1.00

.10
.06
.07
.07
.02

-6.59
-36.89
-30.50
-28.19
-51.38

Time 1 Assessment
1-factor
2-factor
2-factor
2-factor
3-factor

(PS + LK, EP)
(PS + EP, LK)
(PS, LK + EP)
(PS, LK, EP)

117.15***
95.55***
109.05***
103.57***
84.66**

58
56
56
56
53

.87
.91
.88
.89
.93

Time 2 Assessment
1-factor
2-factor
2-factor
2-factor
3-factor

(PS + LK + RD)
(PS + LK, RD)
(PS + RD, LK)
(PS, LK + RD)
(PS, LK, RD)

103.00***
69.08
79.18*
77.09*
51.50

58
56
56
56
53

.90
.96
.95
.95
1.00

Note. All models include scores on the Concepts About Print Test as a measured variable and correlated
residuals between like phonological sensitivity tasks. N = 97. PS = Phonological Sensitivity; LK = Letter
Knowledge; EP = Environmental Print; RD = Word Reading (decoding); S-B^2 = Satorra-Bentler chi-square;
CFI = comparative fit index; RCFI = robust comparative fit index; TLI = Tucker-Lewis index; RMSEA = root
mean square error of approximation; AIC = Akaike information criterion.
* p < . 0 5 . **p<. 01. ***/><.001.

For the older sample's Time 2 assessment (see lower half of
Table 4), the fits of models that included different combinations of
phonological sensitivity, letter knowledge, and text decoding were
compared. These models also included the CAP test as a separate
measured variable. Both chi-square difference tests and evaluation
of the other fit indices indicated that a three-factor model that
included different Phonological Sensitivity, Letter Knowledge,
and Reading (Decoding) factors provided a significantly better fit
than the one-factor model, ^ i f f ( 5 , N = 97) = 51.50, p < .001, a
two-factor model with phonological sensitivity and letter knowledge measures represented by a single factor, Xaiff(3, N =
97) = 17.58, p < .001, a two-factor model with phonological
sensitivity and decoding measures represented by a single factor,
x3iff(3, N = 97) = 27.68, p < .001, and a two-factor model with
letter knowledge and decoding measures represented by a single
factor, ^ i f f ( 3 , N = 97) = 25.59, p < .001, supporting the use of
three separate factors to represent phonological sensitivity, letter
knowledge, and text decoding.
Sample comparisons. To facilitate comparisons between
younger and older samples and to allow preliminary hypotheses
concerning the development of reading-related skills across the
age range covered by both samples (i.e., continuity between the
younger sample's Time 1 assessment and the older sample's
Time 2 assessment), we compared raw scores and measurement
models for the emergent literacy measures from the younger
children at the Time 2 assessment with those from the older
children at the Time 1 assessment. ANOVA revealed that children
in the younger sample at Time 2 were somewhat younger than
children in the older sample at Time 1, F(l, 191) = 4.54, p = .03.
ANOVAs on children's raw scores also revealed that children in
the younger sample at Time 2 scored lower on letter knowledge,
F(l, 191) = 18.86, p < .001, syllable blending, F(l, 191) = 36.87,
p < .001, and phoneme blending, F(l, 191) = 5.18, p = .02, than
did children in the older sample at Time 1 (see Table 1 and Table 2
for descriptive statistics). Differences on phoneme blending were

rendered nonsignificant in an analysis of covariance controlling for
chronological age (p = .16); however, the differences for letter
knowledge and syllable blending remained significant (ps <
.001).3
Multisample CFA was carried out on the data from the younger
children's Time 2 data and the older children's Time 1 data to
examine structural invariance of the three-factor measurement
model across samples (see Table 5). A multisample model with
separate Phonological Sensitivity, Letter Knowledge, and Environmental Print factors, with the CAP test as a separate measured
variable and with none of the parameters across groups constrained
to equality, served as a basis for testing whether adding constraints
to the model across groups would yield a significantly worse fit.
A significant change in the chi-square when factor loadings
were constrained across groups suggested there was a statistically
significant lack of invariance. However, fit indices that are more
robust to sample size supported the invariance of factor loadings,
factor correlations (including correlations with the CAP measure),
and correlated residuals. The comparative fit index (CFI), TuckerLewis Index (TLI), root mean square error of approximation
(RMSEA), and Akaike information criterion (AIC) remained essentially unchanged when these invariance constraints were imposed, and the imposition of all of these constraints did not result
in a significant reduction in the overall model chi-square from the
unconstrained model, ^ i f f (25, N = 193) = 32.79, p > .10.
Consequently, the majority of fit indices indicated that the slight
lack of invariance noted for the factor loadings was of little
3

These significant differences may have been the result of the age range
of the younger group. That is, the youngest child in the older sample
was 60 months old, whereas the youngest child in the younger sample
was 38 months old. Alternatively, these differences may have been a
function of the different preschool environments of the younger and older
samples.

604


Table 5
Fit Indices for Multisample Analysis of Three-Factor Measurement Model for Younger Sample
at Time 2 and Older Sample at Time 1
Model constraints

x2

df

CFI

TLI

RMSEA

AIC

Xdiff

df

None (unconstrained)
Factor loadings
Factor loadings and factor
correlations
Factor loadings, factor
correlations, and correlated
residuals
Factor loadings, factor
correlations, correlated
residuals, and residual
variances

156.98***
176.89***

106
118

.95
.94

.92
.92

.05
.05

-55.02
-59.11

19.91*

10

185.34***

124

.94

.92

.05

-62.66

8.45

6

189.77***

131

.94

.93

.05

-72.23

4.43

7

221.87***

143

.92

.91

.05

-64.13

32.10**

12

Note. All models include scores on the Concepts About Print Test as a measured variable and correlated
residuals between like phonological sensitivity tasks. Chi-square difference tests reflect comparison of a model
with the previous model and thus reflect the change associated with the addition of the specified constraint. N =
193. CFI = comparative fit index; TLI = Tucker-Lewis index; RMSEA = root mean square error of
approximation; AIC = Akaike information criterion.
* p < . 0 5 . ** p < . 01. ***/?<.001.

practical importance and was outweighed by the large gain in
parsimony. In contrast, all fit indices decreased substantially when
item residuals were constrained. Thus, the results indicated that the
measurement model explained children's emergent literacy skills
well across both the younger and older samples of children (i.e.,
the factor structure was equivalent) but that there may have been
systematic sample differences in measurement errors that were of
little substantive interest to the present study.

Longitudinal Prediction Models
Structural equation modeling in EQS was used to examine the
longitudinal relations between emergent literacy and either later
emergent literacy skills (younger sample) or both later emergent
literacy skills and text decoding (older sample). The measurement
models identified in the previous analyses served as the basis for
the longitudinal models. We first calculated the cross-time zeroorder correlations between latent constructs. Because our interest
was in identifying significant sources of influence on children's
development, we began by examining models that included autoregressive paths (i.e., paths between the same factors at different
time points). Inclusion of other paths was guided by results from
analyses of zero-order correlations as well as theoretical considerations. Modifications to these base models were made by examining the results of both (a) Lagrange multiplier (LM) tests, to
determine the value of adding parameters to the models that would
significantly increase the model fit at the p < .05 level, and (b)
Wald tests, to determine the statistical necessity of parameters
whose elimination would not significantly decrease the model fit at
the/? > .10 level.
Younger sample. Zero-order correlations between the latent
variables at Time 1 and the latent variables at Time 2 for the
younger sample of children are shown in the upper half of Table 6.
For the younger sample of children, the base longitudinal prediction model included paths from the Phonological Sensitivity factor
at Time 1 to the Phonological Sensitivity and Letter Knowledge
factors at Time 2. Paths from the Time 1 Oral Language factor to

the Time 2 Phonological Sensitivity factor, the Time 2 Letter
Knowledge factor, the Time 2 Environmental Print factor, and the
Time 2 CAP variable also were included in the model. Finally, a
path from the Nonverbal IQ factor to the Time 2 CAP variable was
included.
On the basis of Wald tests, we dropped the paths from the
Time 1 Phonological Sensitivity factor to the Time 2 Phonological
Sensitivity factor, from the Time 1 Oral Language factor to the
Time 2 Environmental Print factor, and from the Time 1 Noverbal
IQ factor to the Time 2 CAP variable. On the basis of LM tests, we
added paths from the Time 2 Letter Knowledge factor to the
Time 2 Phonological Sensitivity factor, the Time 2 Environmental
Print factor, and the Time 2 CAP variable. The resultant model for
the younger sample is shown in Figure 1, S-B^2(305, N = 96) =
383.05, p < .01, RCFI = .93, RMSEA = .06. Time 2 Phonological Sensitivity was significantly predicted by Oral Language at
Time 1 and Letter Knowledge at Time 2 (R2 = .25). Letter
Knowledge was significantly predicted by both Time 1 Phonological Sensitivity and Time 1 Oral Language (R2 = .20). Environmental Print was significantly predicted by Time 2 Letter Knowledge only (R2 = .45). Finally, scores on the CAP measure at
Time 2 were significantly predicted by both Time 1 Oral Language
and Time 2 Letter Knowledge (R2 = .23).
Because the absence of significant cross-time stability in the
Phonological Sensitivity factor suggested a problem with the measurement of phonological sensitivity at Time 1 for the younger
sample, we examined a model with a Time 1 Phonological Sensitivity factor that included only those tasks with significant crosstime stability (syllable blending and all three elision measures).
Evaluation of the measurement model supported three separate
factors to represent Phonological Sensitivity, Oral Language, and
Nonverbal Cognitive Abilities, S-B^2 (30, N = 96) = 28.83, p =
.53, RCFI = 1.00. There was a significant cross-time correlation
between this reduced Phonological Sensitivity factor and the
Time 2 Phonological Sensitivity factor (r = .35, p < .01). We
examined the full longitudinal model starting with the same base


605

Table 6
Zero-Order Correlations Between Time I Emergent Literacy Skills and Time 2 Emergent
Literacy and Reading Skills for Younger and Older Samples
Time 2 variables
Time 1 variables

Phonological
sensitivity

Letter
knowledge

Environmental
print

Concepts About
Print

.23
.33**
.19

.14
37***
.32*

Reading
.60***
.51**
.51***
.40***

44***
.18
.37**
.62***

Younger sample
Phonological sensitivity
Oral language
Nonverbal cognitive

.14
.36***
.16

.33**
.39***
.15
Older sample

Phonological sensitivity
Environmental print
Letter knowledge

1.00***
.59***
.64***
.60***

.48***
.42***
.80***
.35***

Note. Correlations are between latent variables for each construct, except for the Concepts About Print Test,
which is a measured variable.
* p < . 0 5 . **/><.01. ***/?<.001.

model described previously. The resultant final model is shown in
Figure 2, S-B^(212, N = 96) = 265.74, p < .01, RCFI = .94,
RMSEA = .06. In this modified model, the reduced Time 1
Phonological Sensitivity factor was significantly related to Oral
Language. Time 2 Phonological Sensitivity was significantly predicted by both Phonological Sensitivity and Oral Language at
Time 1 (R2 = .17). Letter Knowledge was significantly predicted
by both Time 2 Phonological Sensitivity and Time 1 Oral Language (R2 = .26). Environmental Print was significantly predicted
by Time 2 Letter Knowledge only (R2 = .49). Finally, scores on
the CAP measure at Time 2 were significantly predicted by
both Time 1 Oral Language and Time 2 Phonological Sensitivity
(R2 = .20).
Older sample. Zero-order correlations between the latent variables at Time 1 and the latent variables at Time 2 for the older
sample of children are shown in the lower half of Table 6. For the
older sample of children, the base longitudinal prediction model
included paths from the Time 2 Phonological Sensitivity and
Letter Knowledge factors to the Reading factor, from the Time 1
Phonological Sensitivity factor to the Time 2 Phonological Sensitivity and the Time 2 Letter Knowledge factors, from the Time 1
Letter Knowledge factor to the Time 2 Letter Knowledge and
Phonological Sensitivity factors, and from the Time 1 CAP measure to the Time 2 CAP measure.4
The paths between the Time 1 Phonological Sensitivity factor
and the Time 2 Letter Knowledge factor and between the Time 1
Letter Knowledge factor and the Time 2 Phonological Sensitivity
factor were dropped on the basis of Wald tests. On the basis of LM
tests, a path between the Time 1 Phonological Sensitivity factor
and the Time 2 CAP variable was added. The resultant model for
the older sample is shown in Figure 3, S-B^2(276, N = 91) =
428.18, p < .001, RCFT = .87, RMSEA = .08. Time 2 Phonological Sensitivity was perfectly predicted by Phonological Sensitivity at Time 1 (R2 = 1.00). Time 2 Letter Knowledge was
predicted by Time 1 Letter Knowledge only (R2 = .72). Scores on
the CAP measure at Time 2 were predicted by scores on the

Time 1 CAP measure and Time 1 Phonological Sensitivity (R2 =
.44). Finally, Time 2 Phonological Sensitivity and Time 2 Letter
Knowledge were the only significant predictors of reading (R2 =
.54). 56 As would be expected from the results of the Wald and LM
tests, when paths between the Time 1 Environmental Print factor,
the Time 2 CAP measure, and the Reading factor were included in
this model, these paths were not significant, indicating that neither
the Environmental Print factor nor the CAP measure added unique
variance to the Reading factor once the Phonological Sensitivity
and Letter Knowledge factors were in the model.
To confirm these findings and to ensure that our model development strategy was not biased against finding significant effects
on reading for the environmental print and print concepts measures, we conducted model testing starting with a base model that
included just the autoregressive paths and paths from both the
Time 1 Environmental Print factor and the Time 2 CAP variable to
the Time 2 Reading factor. The resultant final model following
Wald and LM tests was the model shown in Figure 3, with the
exception that the path between Time 2 Letter Knowledge and

4

The identical final model was obtained when the base model included
paths for all of the Time 1 variables with significant zero-order associations
with Time 2 variables.
5
As would be expected given the high correlations between the Time 1
and the Time 2 Phonological Sensitivity and Letter Knowledge factors,
when the Time 1 Phonological Sensitivity and Letter Knowledge factors
were used to predict the Reading Factor at Time 2, they also accounted for
54% of the variance in decoding.
6
We also tested the unique variance associated with each of the blending
and elision measures by adding (in separate sequential models) a path from
each measure's residual to the Reading factor. In none of these models was
there an improvement in model fit or increment in the R2 for the Reading
factor. These results suggest that, in these data, it was the variance common
to the eight phonological sensitivity measures that was predictive of
decoding rather than the variance unique to the manipulation of phonemes,
syllables, or words.

606


-.61

.48

Figure 1. Structural equation model of longitudinal relations between emergent literacy abilities for younger
sample of children. Circles represent latent variables, and rectangles represent observed variables. Variables on
the left of the figure are from the Time 1 (Tl) assessment (mean age = 41.1 months, SD = 9.4); variables on
the right of the figure represent Time 2 (T2; mean age = 57.6 months, SD = 10.1), reflecting development over
an 18-month period. All paths shown as solid lines are significant at p < .05. Wrd = word-level items, Syl =
syllable-level items, Phon = phoneme-level items, Ltr = letter; Env = environmental; Pics = pictures; CAP =
Concepts About Print Test; PPVT-R = Peabody Picture Vocabulary Tests—Revised; EOWPVT-R = Expressive One-Word Picture Vocabulary Test—Revised; ITPA-VE = Verbal Expression subtest of the Illinois Test
of Psycholinguistic Abilities; ITPA-GC = Grammatical Closure subtest of the ITPA; PicComplet and ObjAssem = Picture Completion and Object Assembly subtests of the Wechsler Preschool and Primary Scales of
Intelligence—Revised.

Reading was not included. An additional model examined the
influence of ITPA-GC scores on the Time 2 factors. In this model,
ITPA-GC scores were not a significant predictor of any Time 2
factor and did not alter the significance of the paths shown in
Figure 3. Finally, we also examined the independence of phonological sensitivity from oral language by regressing ITPA-GC
scores from both reading measures. In this analysis, both the
Phonological Sensitivity and Letter Knowledge factors continued
to be significant and substantial predictors of the Reading factor
(R2 = .39).
Discussion
The results of this study demonstrate that the developmental
origins of a large component of children's reading skills in kin-

dergarten and first grade can be found in the preschool period. A
number of the emergent literacy skills present during the preschool
period (i.e., phonological sensitivity, letter knowledge) reflect
highly stable individual differences and have substantial unique
predictive relations with later reading abilities. Together, phonological sensitivity and letter knowledge accounted for 54% of the
variance in kindergarten and first-grade children's decoding abilities. In contrast, other emergent literacy skills, such as environmental print and print concepts, although present during the preschool period and relatively stable, do not appear to be uniquely
important for children's later reading. Taken together, these results
highlight the developmental continuity between emergent literacy
and later reading from the early preschool period to the early
elementary school period. Additionally, these results provide im-

607


Blend Syl

-.40

jElision W r d i * ^
-.16
-.39

" - ^Elision Syl
-.25'
Vision Phog

PicComplet«
ObjAssem

-,g
..98.

CAP

2. Structural equation model of longitudinal relations between emergent literacy abilities for younger
sample of children including modified Phonological Sensitivity factor for Time 1 assessment. Time 1 measures
included in the modified Phonological Sensitivity factor were those with significant cross-time stability. Circles
represent latent variables, and rectangles represent observed variables. Variables on the left of the figure are from
Time 1 (Tl) assessment (mean age = 41.1 months, SD = 9.4); variables on the right of the figure represent
Time 2 (T2; mean age = 57.6 months, SD = 10.1), reflecting development over an 18-month period. All paths
shown as solid lines are significant at p < .06. Wrd = word-level items, Syl = syllable-level items, Phon =
phoneme-level items, Ltr = letter; Env = environmental; Pics = pictures; CAP = Concepts About Print Test;
PPVT-R = Peabody Picture Vocabulary Tests—Revised; EOWPVT-R = Expressive One-Word Picture
Vocabulary Test—Revised; ITPA-VE = Verbal Expression subtest of the Illinois Test of Psycholinguistic
Abilities; ITPA-GC = Grammatical Closure subtest of the ITPA; PicComplet and ObjAssem = Picture
Completion and Object Assembly subtests of the Wechsler Preschool and Primary Scales of Intelligence—
Revised.

portant information concerning issues of the development and the
measurement of several key emergent literacy skills.
Perhaps the most striking finding from the present study concerned the high level of stability in children's phonological sensitivity. The latent variable representing the phonological sensitivity
of 5-year-old children attending preschool perfectly predicted the
latent variable representing phonological sensitivity of 6-year-old
children attending kindergarten and first grade. These results indicate that there was no change in the ordering or spacing of
children's performance from preschool to kindergarten and first
grade despite the fact that there was significant growth in these
skills (see Table 2). These findings are similar to those found with

older children by Wagner and colleagues (Wagner et al., 1994,
1997). For example, Wagner et al. (1997) reported that year-toyear stability coefficients for their latent phonological sensitivity
variable ranged from .83 (kindergarten to first grade) to .95 (second grade to third grade and third grade to fourth grade). Our
results indicate that this high degree of stability is present earlier in
development and is not the result of formal reading instruction.
In contrast to the extraordinary stability of phonological sensitivity from late preschool to early elementary school, phonological
sensitivity was less stable from early preschool to late preschool.
In fact, very early phonological sensitivity, represented by all eight
measures of the construct we administered, was not a strong or

608


Rhyme
26
^—^Alliteration L

.57

Figure 3. Structural equation model of longitudinal relations between emergent literacy abilities and reading
for older sample of children. Circles represent latent variables, and rectangles represent observed variables.
Variables on the left of the figure are from Time 1 (Tl) assessment (mean age = 60.4 months, SD = 5.4);
variables on the right of the figure represent Time 2 (T2; mean age = 72.9 months, SD = 5.7), reflecting
development over a 13-month period. All paths shown as solid lines are significant atp < .05. Wrd = word-level
items, Syl = syllable-level items, Phon = phoneme-level items, Ltr = letter; Env = environmental; Pic =
pictures; CAP = Concepts About Print Test; ID = identification; Freq = frequent.

unique predictor of phonological sensitivity in the late preschool
period. There was some developmental continuity between this
early phonological sensitivity construct and later phonological
sensitivity; however, this continuity appeared to be mediated by
later letter knowledge, which was a significant concurrent predictor of phonological sensitivity. These results indicate that there
were problems with the measures of phonological sensitivity for
the early preschool group. That is, whatever variance was shared
across all eight measures in the early preschool period was not
phonological sensitivity. Based on the longitudinal empirical relations of this factor, it is possible that the shared variance represented letter knowledge or a proxy measure of print exposure.
When we examined the longitudinal relations of a reduced Phonological Sensitivity factor that included only Time 1 measures
with significant cross-time stability, there was evidence for developmental continuity of the Phonological Sensitivity factor from

early to late preschool. Interestingly, the variables that defined this
reduced factor were mainly those with weak relations to the factor
defined by all eight measures, indicating that the variance shared
between these four variables, and hence the construct represented,
was distinct from that included in the original factor.
Taken together, the results from these two models are similar to
the results from other studies of young children that have found a
predictive relation between phonological sensitivity and later letter
knowledge (Burgess & Lonigan, 1998; Wagner et al., 1994) and
between letter knowledge and both current and subsequent phonological sensitivity (Bowey, 1994; Burgess & Lonigan, 1998;
Johnston, Anderson, & Holligan, 1996; Stahl & Murray, 1994;
Wagner et al., 1994, 1997). The mechanisms by which phonological sensitivity influences the development of letter knowledge and
letter knowledge influences the development of phonological sensitivity are not clear. It is possible that the development of these

skills simply indexes exposure to literacy-related activities. Alternatively, it is possible that children with greater sensitivity to the
phonological structure of words and more letter knowledge may
benefit more from the formal and informal exposure to print that
many preschoolers receive (e.g., Lonigan, 1994; Whitehurst &
Lonigan, 1998). Perhaps the ability to discriminate word and
syllable boundaries makes the significance of letters more transparent. Similarly, understanding the significance of letters may
facilitate the segmentation of language.
In addition to the effects of letter knowledge on phonological
sensitivity, oral language had direct and indirect effects (depending
on the model) on phonological sensitivity in the late preschool
period. This finding is consistent with results from a number of
other studies of both preschool (e.g., Burgess & Lonigan, 1998;
Chaney, 1992; Lonigan et al., 1998) and early elementary school
children (e.g., Bowey, 1994; Wagner et al., 1993, 1997) that have
demonstrated significant concurrent and longitudinal correlations
between children's vocabulary skills and their phonological processing skills. These results suggest that oral language development has an influence on the acquisition of this key emergent
literacy skill. Past studies of preschool children have suggested
that productive phonology (i.e., speech intelligibility) is related to
performance on phonological sensitivity tasks (e.g., Webster &
Plante, 1995). As discussed by Metsala and Walley (1998; see also
Fowler, 1991), this evidence suggests that lexical representations
become more segmental in early childhood as a result of vocabulary growth. The emergence of phonological sensitivity may be
limited by these speech representations.
Despite direct and indirect effects of early oral language and
phonological sensitivity skills, all measured factors accounted for
only 17% to 25% of the variance in phonological sensitivity
measured in the late preschool period. Although these results
indicate that children's phonological sensitivity in the late preschool period is partially a function of early phonological sensitivity, oral language skills, and letter knowledge, they highlight the
fact that the origins of the majority of children's reading-related
phonological sensitivity are unknown. Like the results of our
earlier cross-sectional study (Lonigan et al., 1998), these findings
indicate that significant growth in phonological sensitivity occurs
between 3 and 4 years of age. Consequently, efforts to identify the
origins of phonological sensitivity are likely to be most productive
during this period. Our results also suggest, however, that screening of children for phonological sensitivity deficits is unlikely to
be productive prior to the late preschool period, at least with the
present measures because of their limited predictive power for
later phonological sensitivity.
The results of this study are also informative concerning the
nature of preschool phonological sensitivity. As noted previously,
phonemic sensitivity is often given special status in relation to
reading, with a number of authors arguing that phonemic sensitivity is the critical influence on reading skills (e.g., Morais, 1991;
Muter et al., 1997; Nation & Hulme, 1997; Tunmer & Rohl, 1991).
In contrast, we have argued elsewhere (Anthony & Lonigan, 2000;
Anthony et al., 2000; Lonigan et al., 1998) that it is children's
general sensitivity to the sound structure of language that is important for learning to read an alphabetic system. Our finding that
children's phonological sensitivity, broadly defined (i.e., sensitivity to words, syllables, onset-rime, and phonemes), was best characterized as a unitary construct at each of the four assessments of

609

children across different ages provides strong support for this
position. Even in the reduced factor for the younger children's
Time 1 assessment, Phonological Sensitivity was represented by
sensitivity to words, syllables, and phonemes. Across analyses
from the late preschool and early grade school periods, only one
index of phonological sensitivity did not have a significant association with the phonological sensitivity construct. The wordblending measure did not contribute to the latent variable at the
Time 2 assessment for the older group. This effect was likely due
to the fact that scores on the word-blending measure for the older
children were at near ceiling levels. Regardless, this same analysis
demonstrated that word-level and syllable-level blending were
associated with manipulation of phonemes (i.e., alliteration, phoneme blending, phoneme elision), which supports the broadly
defined phonological sensitivity construct.
Two additional aspects of our results support the importance of
the broader construct of phonological sensitivity. First, whereas
the measures of phonological sensitivity for the younger group's
Time 1 and Time 2 assessments and for the older group's Time 1
assessment were weighted heavily in favor of lower levels of
linguistic complexity (i.e., words, syllables, onset-rime), the measures of phonological sensitivity for the older children's Time 2
assessment were weighted heavily in favor of higher levels of
linguistic complexity (i.e., phonemes). The fact that the earlier
Phonological Sensitivity factor perfectly predicted the later Phonological Sensitivity factor for the older group of children indicates that sensitivity to lower and higher levels of linguistic complexity represents a continuum rather than distinct abilities. These
findings are consistent with the results obtained by Stahl and
Murray (1994), who found that a single-factor solution explained
a majority of the variance in kindergarten children's performance
on four tasks that varied by linguistic complexity.
Finally, the global construct of phonological sensitivity, defined
by variance common to sensitivity to words, syllables, onset-rime,
and phonemes, was a significant and strong predictor of children's
decoding skills. This finding demonstrates that this global phonological sensitivity, rather than just phonemic sensitivity, is influential in the development of children's decoding skills. Moreover,
like other studies (e.g., Bryant et al., 1990; Lonigan et al., 1998;
MacLean et al., 1987; Wagner et al., 1994, 1997), our analyses
demonstrated that this relation was not the result of variance
shared between the global construct of phonological sensitivity
and oral language. That is, the predictive relation between the
global construct of phonological sensitivity and reading is not the
result of children with more developed oral language skills, such as
vocabulary, or general cognitive abilities simply having greater
faculty with tasks assessing broad levels of phonological sensitivity and also having better decoding skills. It is important to note,
however, that our assessment of oral language skills in the older
sample was limited to a single measure. It is possible that other
oral language measures may have shared more predictive variance
with both decoding and phonological sensitivity. However, given
the independence of these constructs demonstrated in the younger
sample and the significant loading of the ITPA-GC on the broader
Oral Language factor, it seems unlikely that additional oral language measures would have substantially weakened the strong
relation between phonological sensitivity and decoding.
Whereas a number of previous studies have interpreted findings
that one measure of phonological sensitivity (e.g., phoneme seg-

610


mentation) predicts reading better than another (e.g., onset-rime
sensitivity) to indicate that one type of phonological sensitivity is
more important to reading than another (Goswami & Bryant, 1990,
1992; Muter et al., 1997; Nation & Hulme, 1997), these analyses
make the explicit or implicit assumption that there are different
types of phonological sensitivity. Our results, as well as the results
of other large studies (e.g., Wagner et al., 1993, 1994, 1997),
demonstrate that such assumptions are incorrect, at least as explanations of the normal development of reading. That is, our analyses of different tasks that varied in linguistic complexity, which
indicated that a single-factor solution provided an excellent fit to
the data, established that these tasks tap the same underlying
ability, phonological sensitivity. Moreover, this single factor predicted a majority of the variance in later decoding skills. These
results are consistent with those of Wagner and colleagues and
Stahl and Murray (1994) in demonstrating that phonological sensitivity is a unitary construct represented by sensitivity to onsetrimes, syllables, and phonemes and in showing that the variance
common to children's abilities to perform tasks requiring sensitivity to onset-rime, syllables, and phonemes is a substantial predictor
of decoding skills.
Our results indicated that, like phonological sensitivity from late
preschool to early grade school, letter knowledge was a very stable
individual difference, and at every assessment, letter knowledge
represented an emergent literacy skill that was independent of
phonological sensitivity, environmental print, and decoding. Letter
knowledge in the late preschool period, indexed by knowledge of
both letter names and letter sounds, predicted 72% of the variance
in kindergarten and first-grade children's letter knowledge. Moreover, this level of stability was likely attenuated because of the
near-ceiling performance of the older children on both the measure
of letter name knowledge and the measure of letter sound knowledge at the Time 2 assessment (see Table 2).
Another significant finding of our study was that measures of
variables that have been the focus of traditional emergent literacy
approaches (i.e., print concepts, environmental print) had no
unique predictive relation to later reading skills or other later
emergent literacy skills. Some emergent literacy advocates have
argued that children's faculty with environmental print demonstrates their ability to derive the meaning of text within context
(e.g., Goodman, 1986); however, other research has not generally
supported a direct causal link between the ability to read environmental print and later decoding skills (Gough, 1993; Masonheimer, Drum, & Ehri, 1984). Although these variables were associated with later reading and later emergent literacy when considered
in isolation (see Table 6), they were not significant unique predictors in the context of letter knowledge and phonological sensitivity. Concepts of print and environmental print might reflect very
early knowledge of literacy; however, our analyses demonstrated
that measures of environmental print reflected a construct that was
distinct from letter knowledge and phonological sensitivity. The
fact that both the environmental print variable and the CAP variable were predicted by phonological sensitivity and letter knowledge suggests that they may best be conceptualized as proxy
measures for these other emergent literacy skills, reflect more
exposure to print and other literacy-related activities (e.g., see
Purcell-Gates, 1996), or both. Two limitations to the conclusions
that can be made concerning print concepts in this study are that
we had only a single indicator of the construct and that we did not

administer the measure to the younger children at Time 1. Consequently, we were unable to represent it as a latent variable, and we
could not estimate its influence on the development of other
emergent literacy skills from the early to the late preschool period.
Although future studies should address these limitations, our findings indicate that what is measured by print concepts that is
independent of letter knowledge and phonological sensitivity is
unrelated to early decoding abilities.
Our analyses revealed that both the measurement models and
the scores obtained by both groups of children during the late
preschool period were nearly identical. Consequently, these findings provide a preliminary means of examining the developmental
continuity of emergent literacy and early reading skills from early
preschool to early grade school. This cross-sample analysis highlights the significance of individual differences in both oral language and phonological sensitivity. That is, individual differences
in oral language skills, such as vocabulary, appear to be an important influence on later emergent literacy skills that are crucial
components for children's development of decoding skills (i.e.,
phonological sensitivity and letter knowledge). Individual differences in phonological sensitivity measured at an early age also
appear to have a significant influence on these key emergent
literacy skills that is independent of oral language abilities.
Despite these significant findings, a number of caveats concerning this study are required. Although the samples used in this study
were larger than those used in most prior studies of preschool
emergent literacy (e.g., Bryant et al., 1990; Chaney, 1992; Fox &
Routh, 1975; Maclean et al., 1987), they were marginally adequate
for structural equation modeling. The broad age range in the
younger sample of children may have obscured potentially important relations between some emergent literacy variables. For instance, it may be that greater stability in phonological sensitivity
emerges at an earlier age but was not apparent because of the age
range of our younger sample. Additionally, our reliance on different samples of children to explore the developmental continuity of
emergent literacy from early preschool to kindergarten and first
grade was not optimal. Although results of multisample analyses
indicated that scores on the measures and the measurement models
were nearly identical across both groups during the late preschool
period, indicating that interpretations across samples were justified, conclusions derived from the same sample would be stronger.
Importantly, it is unlikely that our main findings concerning the
significant relations between emergent literacy skills within and
between assessment phases were the result of the age range of
children within the samples because all analyses were conducted
using scores from which the reliable variance associated with
children's chronological age was statistically removed. However,
these results provide a preliminary examination of how these
different emergent literacy skills relate to each other from the early
preschool period to kindergarten and first grade.
Not all domains of emergent literacy were measured in this
study (Whitehurst & Lonigan, 1998). For instance, some writers
have suggested that the constructs of emergent reading or emergent writing reflect children's developing conceptualizations of
literacy (e.g., Pappas & Brown, 1988; Purcell-Gates, 1988; Sulzby,
1985, 1986, 1988). Although we believe that these skills are likely
to be related to concepts of print and understanding of narratives,
and therefore either reflect dimensions similar to letter knowledge
and phonological sensitivity or relate more strongly to reading


comprehension rather than to decoding (Whitehurst & Lonigan,
1998), future studies should address the relative independence and
specific influences of these emergent literacy skills. In addition to
phonological sensitivity, components of phonological processing,
such as phonological memory and phonological naming, have been
identified in older children as significant correlates of reading
skills (e.g., Bowers & Wolfe, 1993; Wagner et al., 1994, 1997;
Wolfe, 1991). A complete account of emergent literacy will require an understanding of the development of these skills and their
significance, if any, during the preschool years.
Although the results of this study highlight the developmental
continuities and discontinuities in emergent literacy and the significant linkage between emergent literacy skills and later decoding, they do not address the question of the origins of these skills.
Given the significant linkages found in this study, future studies
should address questions concerning the developmental origins of
key skills such as phonological sensitivity and letter knowledge.
Such information will expand our knowledge of emergent literacy
and provide clues for the development of interventions designed to
help children at risk for developing later reading difficulties.
Finally, our results concern the development of emergent literacy
and decoding in children from English-speaking and middle-class
families. Consequently, our results are most relevant to children
learning to read an alphabetic language, and the degree to which
these findings translate to children who may be at risk for reading
difficulties because of conditions associated with poverty or because their native language is not English is unknown.
In summary, the results of this study have extended previous
work on the development of emergent literacy skills and early
reading in several ways. First, our results highlight the developmental continuity between early preschool emergent literacy skills,
later preschool emergent literacy skills, and early reading abilities
of children. Second, these results clarify the nature of readingrelated phonological sensitivity. Contrary to the dominant view
that it is phonemic sensitivity that is critical for decoding, our
results clearly establish that it is children's global sensitivity to
phonological features of language that relates to decoding. Third,
this study partially explains the status of other emergent literacy
skills in explanatory accounts of the development of reading. Skills
such as print concepts or the ability to "read" environmental print
do not appear to have independent predictive associations with
later reading; rather, their predictive relations with later reading
appear to reflect the development of other emergent literacy skills
such as letter knowledge and phonological sensitivity. Finally, the
results of this study highlight the significance of the study of the
origins of preschool emergent literacy skills. The high level of
stability of emergent literacy skills from late preschool to early
grade school, coupled with the lower degree of stability of emergent literacy skills from early preschool to late preschool, suggests
that efforts to identify significant sources of variability between
children in these skills should be directed toward the preschool
years.

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