A brief presentation on important statistics concepts for research proposals. Given for the UQU Medical Research Club "Your Journey Towards Research" held at King Abdullah Medical City, Makkah. May 17, 2012

1. Statistics for Your
Research Proposal
SohailBajammal, MBChB, MSc, FRCS(C), PhD(c)
Assistant Professor of Orthopaedics, Umm Al-Qura University
Director of CME & Research Administration, King Abdullah Medical City Makkah
bajammal

2. What Statistics do you need to know
for your proposal?
• Types of Variables
• Types of Statistics
• How to Choose a Statistical Test?
• Hypothesis Testing & Sample Size

3. Patho Physiology of Research
Research Study Plan Actual Study
Question Design Implement
Target Intended
Actual subjects
Population Sample
Errors Errors
Actual
Phenomena Intended
measurements
of interest variables
Truth in the Truth in the Findings in
Universe Infer Study Infer the Study
External Validity Internal Validity
From Hulley et al. Designing Clinical Research. LWW

4. Variables

5. Variables
• Anything whose value can vary
• Dependent (response) variable: outcome
• Independent (explanatory) variables: predictors
• Confounding variable: associated with the
independent variable and a cause of the dependent
variable
– coffee drinking (independent), MI (dependent)
– cigarette smoking (confounder),

6. Types of
Variables
Categorical Quantitative
(Continuous or
“Qualitative” Discrete)
Nominal Ordinal Interval Ratio
Nationality Stage I, II, III Temperature Pulse
Gender & IV cancer (0 is not zero) (0 is dead)

7. Types of
Variables
Categorical Quantitative
(Continuous or
“Qualitative” Discrete)
Nominal Ordinal Interval Ratio
Nationality Stage I, II, III Temperature Pulse
Gender & IV cancer (0 is not zero) (0 is dead)

8. Types of
Variables
Categorical Quantitative
(Continuous or
“Qualitative” Discrete)
Nominal Ordinal Interval Ratio
Nationality Stage I, II, III Temperature Pulse
Gender & IV cancer (0 is not zero) (0 is dead)

9. Types of
Variables
Categorical Quantitative
(Continuous or
“Qualitative” Discrete)
Nominal Ordinal Interval Ratio
Nationality Stage I, II, III Temperature Pulse
Gender & IV cancer (0 is not zero) (0 is dead)

10. Implications of Types of Variable
• Details of data collection forms
– Age:
• ……. Years Ratio
• <20yr, 21-30yr, 31-40yr, >40 Ordinal
• Choice of statistical analysis test
• Coding in the statistical software: 1,2 for nominal
– Does not make sense to have a mean for nominal
• BIAS if you didn’t consider confounders

11. When deciding on your variables
• Think of patient-oriented outcomes, instead of
disease-oriented outcomes
• Studying the effect of new drugs on
arrhythmia, which is better as outcome?
– Number of arrhythmia
– Frequency of palpitation/Quality of Life

12. Statistics

13. Statistics deals with
• Collection
• Organization
• Analysis
Data
• Interpretation

14. Types of Statistics
Statistics
Descriptive Inferential
Statistics Statistics
Measures
Measures What Confidence
of Central Interval
of Spread test?
Tendency
Inter-
Standard
Mean Median Mode quartile
Deviation
Range

15. Types of Statistics
Statistics
Descriptive Inferential
Statistics Statistics
Measures
Measures What Confidence
of Central Interval
of Spread test?
Tendency
Inter-
Standard
Mean Median Mode quartile
Deviation
Range

16. Types of Statistics
Statistics
Descriptive Inferential
Statistics Statistics
Measures
Measures What Confidence
of Central Interval
of Spread test?
Tendency
Inter-
Standard
Mean Median Mode quartile
Deviation
Range

17. Descriptive Statistics
• Numerical
• Tabulated
• Graphs

18. Measures of Central Tendency
• Mean: average
• Mode: most frequent count
• Median: the value separating the top and
bottom of data (organized highest to lowest)

19. Measures of Central Tendency
Best measure of
Type of Variable
central tendency
Nominal Mode
Ordinal Median
Interval/ratio
Mean
(not skewed)
Interval/ratio
Median
(skewed)

20. Difficult Exam Scores!!
Laerd.com

21. Measures of Spread (Variability)
• Standard Deviation
• Percentile
• Range &Interquartile Range

22. Standard Deviation
Variability of values
around the mean
Variance
Standard
Deviation
Courtesy of Prof. Hassan Baaqeel

23. Differences in Standard Deviation
Bell-shaped curve
0.08
0.07 Mean = 70 SD = 5
0.06
0.05
Density
0.04
Mean = 70 SD = 10
0.03
0.02
0.01
0.00
40 50 60 70 80 90 100
Grades

24. Normal Distribution
MEAN
68 % of
observations 1 SD
2 SD
95 % of observations
99.7 % of observations 3D
-3 -2 -1 0 1 2 3
STANDARD DEVIATIONS
Courtesy of Prof. Hassan Baaqeel

25. Types of Statistics
Statistics
Descriptive Inferential
Statistics Statistics
Measures
Measures What Confidence
of Central Interval
of Spread test?
Tendency
Inter-
Standard
Mean Median Mode quartile
Deviation
Range

26. Inferential Statistics
• Allow for making predictions, estimations or
inferences about what has not been observed
(the whole population) based on what has
(the sample)
• Every time we use inferential statistics we risk
being wrong by chance
– We need a range of values to be confident
(Confidence Interval)

27. Patho Physiology of Research
Research Study Plan Actual Study
Question Design Implement
Target Intended
Actual subjects
Population Sample
Errors Errors
Actual
Phenomena Intended
measurements
of interest variables
Truth in the Truth in the Findings in
Universe Infer Study Infer the Study
External Validity Internal Validity
From Hulley et al. Designing Clinical Research. LWW

28. Hypothesis Testing
• When we compare two groups, we are testing a
hypothesis
• Null Hypothesis (HO):
– there is no difference between the groups
– (e.g., no difference in mortality)
• Alternate Hypothesis (HA):
– there is a difference
• We choose a statistical test to do the hypothesis testing

29. Chi-square
Mann-Whitney
Statistical Tests
t-test
Kruskal-Wallis
ANOVA

30. How to Choose a Statistical Test?
• Your Question:
– Difference between groups or correlation/prediction
• Variables:
– Types: nominal, ordinal, interval or ratio
– Distribution: normal or skewed
• Groups:
– Number: two or more
– Relationship: related or un-related

31. Brookes University

32. Bates College

33. Probably the simplest/coolest
City College Coventry

36. Choice of Statistical Tests
Parametric Non-Parametric
Tests Tests
Interval/Ratio 1. Ordinal
Goal (normal 2. Interval/Ratio Nominal
distribution) (skewed)
Comparison of 2
Unpairedt-test Mann-Whitney U
unrelated groups
Chi-square Test
Comparison of >2
ANOVA Kruskal-Wallis H
unrelated
Comparison of 2
Paired t-test Wilcoxon
related groups
Binomial Sign Test
Comparison of >2 Repeated measures
Friedman
related groups ANOVA
Correlation Pearson’s Spearman’s rho Chi-square Test

37. All the inferential tests are “estimation”
• We need a CONFIDENCE INTERVAL
• It is a range of values that if the estimate
occurs in this range, we will be confident that
it is not due to chance
• How much error are we willing to accept ?
– α< 0.05

38. Paul Mathews, Design of Experiments with MINITAB, 2005, ASQ Press

39. Hypothesis Testing (α&β errors)
Null Hypothesis: No association between predictor & outcome
Truth in the Population
Results in the
Study Sample Association Between No Association Between
Predictor & Outcome Predictor & Outcome
Reject null
Correct Type I error (α)
hypothesis
Fail to reject null
Type II error (β) Correct
hypothesis

40. Type I & II Errors
• Type I (α) Error: usually 1-5%
– Rejecting the null hypothesis when it is actually true
– Stating that there is a difference, while in truth there is no
difference
• Type II (β) Error: usually 10-20%
– Failing to reject null hypothesis when it is actually false
– Stating that there is no difference, while in truth there is a
difference
– Statistical Power of the Study = 1-β

42. Zazzle.com

43. Resources

44. What do you need to know
in statistics for your proposal?
• Types of Variables
• Types of Statistics
• How to Choose a Statistical Test?
• Sample Size
bajammal