This document discusses variables, hypotheses, study types, and validity/reliability in research. It defines variables as characteristics that can take different values, and categorizes them as numerical, categorical, continuous, discrete, ordinal, and nominal. Hypotheses predict relationships between factors and problems that can be tested. Study types include descriptive studies, comparative/analytical studies, experimental studies, quasi-experimental studies, and before-after studies. Validity means measurements actually assess what is intended, while reliability means repeatability of findings.

1. Variables & Study Types
Aman Ullah

2. ALERT: The materials included in this
presentation was actually taught by
Dr. Tasleem Akhtar
in the contact session of Master in
Health Research at Khyber medical
university, Peshawar, Pakistan

3. HYPOTHESES
Based on your experience with the study
problem, it might be possible to develop
explanations for the problem, which can
then be tested.
A HYPOTHESIS is a prediction of a
relationship between one or more factors
and the problem under study that can be
tested.

4. VARIABLES
A Variable is a characteristic of a person,
object or phenomenon which can take on
different values.
Example of a variable
•Age
•weight
•distance
•Income etc

5. Types of Variables:
•Numerical:
The values of all these variables are
expressed in numbers
•Categorical:
These variables can only be expressed in
categories.

6. Numerical variables can either be
continuous or discrete.
•Continuous.
•Discrete.

7. •Continuous
A continuous variable is one for which,
within the limits the variable ranges, any
value is possible.
With this type of data, one can develop
more and more accurate measurements
depending on the instrument used, e.g.
height (CM) , temperature (degrees),

8. •Discrete
These are variables in which numbers
can only have full values, e.g. number of
visits to a clinic, family members
•

9. Categorical variables can either be
1. ordinal or
2. nominal.
• Ordinal variables: These can be
Grouped and
Ordered or ranked in increasing or
decreasing order

10. • Nominal variables:
These can be grouped only
Cannot be ordered or ranked

11. Operationalising variables by
choosing appropriate indicators
Operationalising variables means that you
make them ‘measurable’ with one or more
precise INDICATORS.
Examples: Level of Knowledge, Socio-
economic status, IQ, awareness about a
problem etc

12. Defining variables and indicators of
variables
To ensure that everyone understands
exactly what has been measured and to
ensure that there will be consistency in the
measurement, it is necessary to clearly
define the variables (and indicators of
variables).

13. Dependent and independent
variables
Because in health research you often
look for causal explanations, it is
important to make a distinction between
dependent and independent variables.
Contd.

14. Dependant Variable
The variable that is used to describe or
measure the problem under study is
called the Dependent variable (The effect
variable).

15. Independent Variable
The variables that are used to
describe or measure the factors that
are assumed to cause or at least to
influence the problem are called the
Independent variables (cause
variable).

16. Confounding Variable
A variable that is associated with the
problem and with a possible cause of the
problem is a potential Confounding
Variable.

18. A confounding variable may either
strengthen or weaken the apparent
relationship between the problem and a
possible cause.
For example:
A relationship is shown between bottle-
feeding and diarrhea in under-twos.
However, mother’s education may be
related to bottle-feeding as well as to
diarrhea.

19. STUDY TYPES
Several classifications of study types are
possible, depending on what research
strategies are used. Generally there are
two broad categories:
1. Non- intervention Studies
2. Intervention Studies

20. 1. Non-intervention studies in which
the researcher just observes and
analyses researchable objects or
situations but does not intervene
2. Intervention studies in which the
researcher manipulates objects or
situations and measures the
outcome of his manipulations

21. NON-INTERVENTION STUDIES
•Descriptive studies
•Comparative (analytical) studies

22. Descriptive studies
A Descriptive Study involves describing
the characteristics of a particular situation,
event or case.
•Small scale, descriptive case studies
•Large scale, cross-sectional surveys
•A stuy hat covers the total population is
called a census.

23. Comparative or analytical studies
An Analytical Study attempts to establish
causes or risk factors for certain
problems. This is done by comparing two
or more groups, some of whom have the
problem and some have not.

24. Types of analytical studies

25. Cross-sectional comparative studies
Two groups, one with the problem and
another without it, are taken from the same
population and compared for the presence
of the independent variables/influencing
factors, for the problem under study, at
one point in time.
In any comparative study, one has to
watch out for Confounding or Intervening
variables.

26. Case-control studies
In a Case-Control Study the investigator
compares one group among whom the problem
that he wishes to investigate is present, called
the study group and
Compares it with another group without the
problem, called the control group
Each case in the study group is matched with a
control in the control group for background
variables

27. Diagram of a case-control study

28. Cohort studies
In a Cohort Study, a group of individuals that is
exposed to a risk factor (study group) is
compared to a group of matched individuals not
exposed to the risk factor (control group).
The researcher follows both groups over time
and compares the occurrence of the problem
that he expects to be related to the risk factor in
the two groups

29. Diagram of a cohort study

30. INTERVENTION STUDIES
In intervention studies, the researcher
manipulates a situation and measures the effects
of this manipulation.
Types of intervention studies :
•Experimental studies and
•Quasi-experimental studies.
•Before and after studies

31. Experimental studies
In an Experimental Study, individuals are
randomly allocated to at least two groups.
One group is subject to an intervention, or
experiment,
while the other group(s) is not.
The outcome of the intervention (effect of the
intervention(independent variable) on the
dependent variable/problem) is determined

32. Diagram of an experimental study

33. Quasi-experimental studies
In a Quasi-Experimental Study, one
characteristic of a true experiment is
missing, either randomisation or the use of
a separate control group.
A quasi-experimental study, however,
always includes the manipulation of an
independent variable which is the
intervention.

34. Diagram of a quasi-experimental design

35. Before-after study
Another type of design that is often chosen
because it is quite easy to set up uses only one
group in which an intervention is carried out.
The situation is analysed before and after the
intervention to test if there is any difference in
the observed problem.

36. Diagram of a before-after study

37. VALIDITY AND RELIABILITY
What are validity and reliability in research
findings?
Validity means that your scientific observations
actually measure what they intend to measure
(your conclusions are true).
Reliability means that someone else using the
same method in the same circumstances should
be able to obtain the same findings (your
findings are repeatable).

39. Questions/Suggestions
khurramthalwi@hotmail.com