6. “
1. Capable of assuming several values
2. Values arise from measurement
3. Useful for statistical purposes
4. One variable value predictable on basis of another
5. Verifiable
6
7. Types of Variables in Medicine
• Clinical Measures (GS available):
Grades of Dyspnea, JVP, Ascites, Hepatomegaly, ECG,
Blood Urea
• Clinical Measures (GS not available):
Pain, Dis-satisfaction, Disability,
• Clinical Indices: Diagnostic index, Prognostic index,
• Therapeutic index
• Measures Performance:
Sensitivity, Specificity, LR
• Epidemiological: Infant mortality,
Incidence
• Statistical Measures: SD, OR,
p value
12. Characteristics
◦ Believed to affect the dependent variable
◦ Researcher can control & manipulate
◦ Predictor or Experimental
Independent
Variable
IV
12
13. Characteristics
◦ Changes (Effects) researcher interested
◦ Dependent on an independent
variable(s)
◦ Outcome variable
Dependent
Variable
DV
13
14. DV should be sensible and they
should be clinically important, but
also related to the IV
14
16. Characteristics
◦ A hypothetical variable
◦ Explain causal links between
other variables
◦ Precedes causal sequence
◦ Hypothetical constructs (
personality, intelligence or
attitude)
◦ Mediator/ intermediary
variable
◦ Cannot be measured directly
16
Cause Mediator Effect
Poverty Health Care Life Expectancy
18. Control Variable
Variable or an element
which is held constant
throughout an
experiment or a research
in order to assess the
relationship between
multiple variables.
18
21. A Situation in
which the effect
or association
between
exposure and
outcome is
distorted by the
presence of
another variable
Confounding
Variable
Outcome
Variable
Explanatory
Variable
Confounding
Variable
Confounding
Variable
Mediator
Variable
Mediator
Variable
24. 24
Prejudice
1. Study observes a statistical tendency for children born fourth or later on order among
their siblings (exposure) and having Down’s syndrome (outcome)
Exposure
Birth order 4th or
higher
Outcome
Birth of an infant
with Down’s
syndrome
Confounder
Maternal age
>35 years
2. When marital age is taken into account, it becomes clear that higher birth order is linked to
higher maternal age, and that maternal age is a more plausible causal factor for Down’s
syndrome
3. Adjusting statistically for maternal age causes the association between birth order and
Down’s syndrome to disappear, suggesting that maternal age was indeed, a confounding
25. 25
Third Variable
Mixing of Effects
Modify
Outcome
Increase
Outcome
Decrease
No Effect Confound
Both Modify
& Confound
Synergism Antagonism
28. Associated with both
risk factor & outcome
Distributed unequally
among groups
Not an intermediary
step in causal pathway
A causal risk factor
among unexposed
Risk Factor
Is the color of
gold, butter and
ripe lemons. In
the spectrum of
visible light,
yellow is found
between green
and orange.
Preventive
Factor
Is the colour of
the clear sky
and the deep
sea. It is located
between violet
and green on
the optical
spectrum.
Surrogate /
Marker
Is the color of
blood, and
because of this
it has historically
been associated
with sacrifice,
danger and
courage.
28
29. Identification
of
Confounders
Compare the estimated measure of
association before and after adjusting for
confounding. If the difference is ≥10%, then
confounding
If there is a clinically meaningful relationship
between an the variable and the risk factor
and between the variable and the outcome ,
the variable is regarded as a confounder
Tests of hypothesis to assess whether the
variable is associated with the exposure of
interest and with the outcome
33. 33
Similar to (but not exactly the same as) dependent variables
Have values that are determined by other variables in the system
“other” variables are called exogenous variables)
Endoge
nous
