Evaluation of evidence [compatibility mode]

EVALUATION OF EVIDENCE
Shikur MohammedShikur Mohammed
(BSc, MPH)
2/2/2015 1By Shikur Mohammed (BSc, MPH)

Evaluation of Evidence
Evaluation is a process of determining the
usefulness, reliability and validity of something
against explicit predetermined standards

Common Problems in observed findings
Inadequacy of the observed sample (The role of
chance)
Inappropriate selection of study subjects & unfair
data collection methods (Bias)data collection methods (Bias)
Comparing unequal (Confounding)

1. The role of chance
The larger the sample on which the estimate is
based, the less variability and the more reliable the
inference
This is done by performing an appropriate test of
statistical significancestatistical significance
A measure that is often reported from all tests of
statistical significance is the P-value

The role of chance cont…
P < 0.05 - statistically significant
P > 0.05 – no statistically significant association (
chance can not be excluded as a likely explanation)chance can not be excluded as a likely explanation)

The role of chance cont…
It is always advisable to report the actual P-value
rather than merely that the results did or did not
achieve statistical significanceachieve statistical significance
confidence interval (CI) is far more informative
measure than P-value to evaluate the role of chance

Bias
It is any systematic error in the design, conduct or
analysis of a study
Types of biasTypes of bias
1. Selection bias,
2. Information (Observation) bias

1. Selection bias
It is a bias introduced while selecting the study
participants
It is a particular problem in case control andIt is a particular problem in case control and
retrospective cohort studies. E.g. If the way in
which participants are selected into the study is
different for cases and controls

Examples of selection bias
a) Diagnostic bias: Diagnostic approach related to
knowing exposure status
For example
women who take oral contraceptives (OCs) may be
screened more often for breast cancer than women who
do not take OCs because of the suspected link between
oral contraceptive and breast cancer

selection bias…
b). Volunteer bias/ Compliance bias: People who
accept to participate in a study or people who refuse
to participate are often quite different from the
general population
c). Non-response bias: This is due to differences in thec). Non-response bias: This is due to differences in the
characteristics between the responders and non-
responders to the study

selection bias cont…
d). Loss to follow up: Difference in completeness of
follow-up between comparison groups
e). Berkson’s bias: Studies carried out exclusively in
hospital settings are subject to selection biashospital settings are subject to selection bias
attributable to the fact that risks of hospitalization
can combine in patients who have more than one
condition

Ways of minimizing selection bias
• Population-based studies are preferable
• Avoid the inclusions as study subjects of people
who have volunteered on their own
In case-control study, it is useful to select several• In case-control study, it is useful to select several
different control groups
• keep losses to follow-up to minimum

2. Information/Observation bias
Refers to bias which arises during the data collection
process
It occur because of mistakes in categorizing studyIt occur because of mistakes in categorizing study
subjects with respect to their exposure or disease
status

Examples of information bias
a) Investigator bias/ Interviewer bias/ Observer bias:
Occurs when investigators collect information
differently in different comparison groups
b) Response bias/Recall bias: Occurs as a result of
difficulty to recall prior exposuresdifficulty to recall prior exposures
c) Social desirability bias: Occurs because subjects are
systematically more likely to provide a socially
acceptable response

Examples information bias….
d). Placebo effect: tendency for individuals to report favorable
response to any therapy regardless of the physiologic efficacy
of what they received
e). Hawthorn effect: Refers to the change in the dependent
variable which may be due to the process of measurement or
observation itself

Ways of minimizing information bias
Blinding: the study subjects doesn't know to which
group they are assigned
using placebo: Use of placebo minimizes the bias in the
ascertainment of both subjective disease outcomes and
side effects. It facilitates that both groups in the study
gain equal attention
Using standard procedures, instruments, questionnaires,
interviewing techniques

Confounding
Confounding variable is a variable that can cause or
prevent the outcome of interest, is not an
intermediate variable, and is associated with the
factor under investigation

Confounding …
Confounding variable must fulfill each of the
following criteria:
1. the variable must be associated with the exposure and,
independent of that exposure, be a risk factor for the
diseasedisease
2. The distribution (frequency) of the confounding variable
should vary between the groups that are compared
3. Confounder must not be an intermediate link in a causal
pathway between exposure and outcome

Confounding …….Example
An observed association between drinking alcohol
and increased risk of lung cancer (LC) could be due
to the effect of cigarette smoking, since alcohol
drinking is associated with smoking and,drinking is associated with smoking and,
independent of alcohol consumption, smoking is a
risk factor for LC

Control for Confounding VariablesControl for Confounding VariablesControl for Confounding VariablesControl for Confounding Variables
In the design:
• Randomization
• Restriction
• Matching
During analysis:During analysis:
• Standardization
• Stratification
• Multivariate analysis

Establishing causal relationships
The following formal criteria are widely used to evaluate the
likelihood that an association is causal
1. Strength of the association
2. Dose-response relationship
3. Consistency of the relationship3. Consistency of the relationship
4. Temporal relationship
5. Specificity of the association
6. Biological plausibility (coherence with existing
information)
7. Prevention

Conclusion about causation
The above criteria are the ones most frequently employed in
trying to establish causation
None provides in itself a perfect means of providing
causation, and each has its limitationscausation, and each has its limitations
However, when they are considered together, the weight of
the evidence may allow a tentative conclusion to be reached

Evaluation of evidence [compatibility mode]

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