experimental designs

1. UNIT 4 ( b) EXPERIEMNTAL
DESIGN
Ms. Chanda Jabeen
Lecturer
RN, RM, BSN
M.Phil. Epidemiology & Public Health
PhD (Scholar) Epidemiology & Public Health
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2. Objectives
At the end of this presentation students will be able
• To understand different pre experimental design.
• To discuss the various types of experimental design
– Post-test-only Control Design
– Pretest-post-test-only Design
– Solomon Four-group Design
– Factorial Design
– Randomized Block Design
– Crossover Design
– Randomized Controlled Trials
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3. Pre-Experimental Design
Pre-experimental designs are so named
because they follow basic experimental steps
but fail to include a control group.
In other words, a single group is often
studied but no comparison between an
equivalent non-treatment group is made.
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4. TYPES OF PRE-EXPERIMENTAL
RESEARCH DESIGN:
o One-shot case design
o One-group pretest-posttest design
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5. ONE-SHOT CASE DESIGN
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 In this research design, a single experimental
group is exposed to a treatment & observations
are made after the implementation of that
treatment.
 There is no random assignment of subjects to the
experimental group & no control group at all.
Exp. group Treatment Post-test

6. ONE-GROUP PRETEST-POSTTEST
DESIGN
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 It is the simplest type of pre-experimental design,
where only the experimental group is selected as
the study subjects.
 A pretest observation of the dependant variables is
made before implementation of the treatment to the
selected group, the treatment is administered, &
finally a posttest observation of dependant variables
is carried out to assess the effect of treatment on the
group.

7.  Some researcher also argue this design as sub
type of quasi-experimental research design.
However in absence of both randomization &
control group.
 This design ethically can not be placed under the
classification of quasi-experimental research
design.
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8. COUNT…
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Exp. group Pretest Treatment Post-test

9. True Experimental design
A true experimental design is one in which
the researcher manipulates the Independent
Variable (or variables) to observe its effect on
some behavior or cognitive process (the
dependent variable) while using random
assignment of participants to groups in order
to control external factors from influencing
the results.
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10. True experimental design is regarded as the
most accurate form of experimental research,
in that it tries to prove or disprove a
hypothesis mathematically, with statistical
analysis.
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11. TYPES OF TRUE EXPERIEMNTAL
DESIGN
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True Experimental Design
Post-test
only
Factorial
Pretest post-
test only
Crossover
Solomon 4
groups
Randomize
block

12. 1. POST-TEST-ONLY CONTROL
DESIGN
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 Composed of two randomly assigned group, i.e.
experimental & control, but neither of which is
pretested before the implementation of treatment
on the experimental group.
 In addition, while treatment is implement on the
experimental group only, post-test observation is
carried out on both the group to assess the effect
of manipulation.

13.  This design can be helpful in situations where it
is not possible to pretest the subjects.
 For example, to study the effect of an
educational intervention related to urinary
incontinence on them subsequent help-
seeking behavior of older adults.
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14. Random
Assignmen
t
Exp. group Treatment Post-test
Control group Post-test
POST-TEST-ONLY CONTROL
DESIGN
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15. 2. PRETEST-POST-TEST-ONLY
DESIGN
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 In this research designs, subjects are randomly
assigned to either the experimental and the control
group.
 The effect of the dependent variable on both the
groups is seen before the treatment (pretest).
 Later, the treatment is carried out on experimental
group only, & after-treatment observation of
dependant variable is made on both the groups to
examine the effect of the manipulation of
independent variable on dependant variable.

16. • For example, such a design could be used
for ‘an experimental study to assess the
effectiveness of cognitive behavioral
therapy interventions for patients with
breast cancer.’
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17. Exp.
group Treatment Post- test
Control
group
Post-test
pretest
pretest
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Random
Assignment

18. 3. SOLOMON FOUR-GROUP
DESIGN
1. Pre-test, treatment, post-test
2. Pre-test, no treatment, post-test
3. Treatment, post-test
4. No treatment, post-test
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19. 19
 There are two experimental groups (experimental
group 1 & experimental group 2) & two control
groups (control group 1 & control group 2).
 Initially, the investigator randomly assigns subjects
to the four groups.
 Out of the four groups, only experimental group
1 & control group1 receives the pretest,
followed by the treatment to the experimental
group 1 & experimental group 2.

20. • Finally, all the four groups receive post-test,
where the effects of the dependent variables of
the study are observed & comparison is made
of the four groups to assess the effect of
independent variable (experimental treatment)
on the dependent variable.
• In this, experimental group 2 was observed at
one occasion, & that score should be similar to
average scores of those in experimental &
control groups.
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21.  Toestimate the amount of change in experimental
& control group 2, the average test scores of
experimental & control groups 1 are used as
baseline
 The solomon four-group design is believed to be
most prestigious experimental research design,
because it minimizes the threat to internal &
external validity.
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22. COUNT…
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Random
assignment
Exp. Group 1
Control Group 1
Exp. Group 2
Control Group 2
pretest treatment Post-test
pretest Post-test
treatment Post-test
Post-test

23. 4. FACTORIAL DESIGN
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 In factorial design, researcher manipulates two or
more independent variables simultaneously to
observe their effects on the dependant variables.
 This design is useful when there are more than two
independent variables, called factors to be tested.
 For example, a researcher wants to observe the
effect of two different protocols of mouth care on
prevention of VAP when performed at different
frequencies in a day.

24.  This design also facilitates the testing of several
hypothesis at a single time.
 Typical factorial design incorporates 2X2 or
2X3 factorial, but it can be in any combination.
 The first number (α) refers to the independent
variables or the type of experimental treatments,
& the second number (β) refers to the level or
frequency of the treatment.
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25. Frequency of
mouth care
Protocols of the mouth care
Chlorhexidine
(α1)
Saline (α2)
4 hourly (β1) α1….β1 α2….β1
6 hourly (β2) α1….β2 α2….β2
8 hourly (β3) α1….β3 α2….β3
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26. Examples of Factorial Designs
• A university wants to assess the starting salaries
of their MBA graduates. The study looks at
graduates working in four different employment
areas: accounting, management, finance, and
marketing. In addition to looking at the
employment sector, the researchers also look at
gender. In this example, the employment sector
and gender of the graduates are the independent
variables, and the starting salaries are the
dependent variables. This would be considered a
4×2 factorial design.
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27. • Researchers want to determine how the amount of
sleep a person gets the night before an exam impacts
performance on a math test the next day. But the
experimenters also know that many people like to
have a cup of coffee (or two) in the morning to help
them get going. So, the researchers decide to look at
how the amount of sleep and the amount of caffeine
influence test performance. The researchers then
decide to look at three levels of sleep (4 hours, 6
hours, and 8 hours) and only two levels of caffeine
consumption (2 cups versus no coffee). In this case,
the study is a 3×2 factorial desig
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28. 5. RANDOMIZED BLOCK DESIGN
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 Control of inherent differences between
experimental subjects & differences in
experimental conditions is one of the difficult
problems faced by researcher in biological
sciences.
 When there are a large number of experimental
comparison groups, the randomized block design
is used to bring homogeneity among selected
different groups.

29. • This is simple method to reduce the variability
among the treatment groups by a more
homogeneous combination of the subjects through
randomized block design.
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30.  For example, a researcher wants to examine the
effects of three different antihypertensive drugs on
patients with hypertension.
 In this example, to ensure the homogeneity
among the subjects under
treatment, researcher randomly places the subjects
in homogeneous groups (blocks) like patients with
primary hypertension, diabetic patients with
hypertension, & renal patients with hypertension .
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31. Types of
antihypertensiv
e drugs
Blocks
Patients with
primary
hypertension
(I)
Diabetic
patients with
hyper tension
(II)
Renal
patients with
hypertension
(III)
A A, I A, II A, III
B B, I B, II B, III
C C, I C, II C, III
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32. 6. CROSSOVER DESIGN
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 In this design, subjects are exposed to more
than one treatment, where subjects are
randomly assigned to different orders of
treatment.
 It is also known as ‘repeat measures design’.
 This design is more efficient in establishing
the highest possible similarity among
subjects exposed to different conditions,
where groups compared obviously have
equal distribution of characteristics.

33. • Through crossover design is considered as an
extremely powerful research design, sometimes
it is not effective because when subjects are
exposed to two different conditions, their
responses of the second condition may be
influenced by their experience in the first
condition.
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34.  For example, when we are comparing the
effectiveness of the chlorhexidine mouth care protocol
on group I & saline mouth care protocol on the subjects
of group II.
 Later, the treatment is swapped, where group I
receives the saline mouth care & group II receives
chlorhexidine. In such studies, subjects serve as their
own control.
Groups Protocols of the mouth care
Group I Chlorhexidine (α1) Saline (α2)
Group II Saline (α2) Chlorhexidine (α1)
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37. RANDOMIZED CONTROLLED
TRIALS
The randomized controlled trial (RCT) is noted to
be the strongest methodology for testing the
effectiveness of a treatment because of the elements
of the design that limit the potential for bias.
Subjects are randomized to the treatment and
control groups to reduce selection bias.
In addition, blinding or withholding of study
information from data collectors, participants, and
their healthcare providers can reduce the potential
for bias.
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38. RCTs, when appropriately conducted,
are considered the gold standard for determining
the effectiveness of healthcare interventions.
RCTs may be carried out in a single setting or in
multiple geographic locations to increase sample
size and obtain a more representative sample.
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39. The initial RCTs conducted in medicine
demonstrated inconsistencies and biases.
Consequently, a panel of experts—clinical trial
researchers, medical journal editors,
epidemiologists, and methodologists—developed
guidelines to assess the quality of RCTs reports.
This group initiated the Standardized Reporting of
Trials (SORT) statement that was revised and
became the CONsolidated Standards for Reporting
Trials (CONSORT). This current guideline includes
a checklist and flow diagram that might be used to
develop, report, and critically appraise published
RCTs.
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40. • An RCT needs to include the following elements:
1. The study was designed to be a definitive test of
the hypothesis that the intervention caused the
defined dependent variables or outcomes.
2. The intervention is clearly described and its
implementation is consistent to ensure intervention
fidelity.
3. The study is conducted in a clinical setting, not in
a laboratory.
4. The design meets the criteria of an experimental
study.
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41. 5. Subjects are drawn from a reference population through
the use of clearly defined criteria. Baseline states are
comparable in all groups included in the study. Selected
subjects are then randomly assigned to treatment and
comparison groups thus, the term randomized controlled
trial.
6. The study has high internal validity. The design is
rigorous and involves a high level of control of potential
sources of bias that will rule out possible alternative
causes of the effect. The design may include blinding to
accomplish this purpose. With blinding the patient, those
providing care to the patient, and/or the data collectors are
unaware of whether the patient is in the experimental
group or in the control group.
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42. 7. Dependent variables or outcomes are measured
consistently with quality measurement methods.
8. The intervention is defined in sufficient detail so that
clinical application can be achieved.
9. The subjects lost to follow-up are identified with their
rationale for not continuing the study.
The attrition from the experimental and control groups
needs to be addressed, as well as the
overall sample attrition.
10. The study has received external funding sufficient to
allow a rigorous design with a sample size
adequate to provide a definitive test of the intervention.
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44. Trial registration site
• www.clinicaltrial.gov
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48. QUASI-EXPERIMENTAL DESIGN
A quasi-experiment is an empirical interventional
study used to estimate the causal impact of an
intervention on target population without random
assignment.
Quasi-experimental research shares similarities
with the traditional experimental design or
randomized controlled trial, but it specifically lacks
the element of random assignment to treatment or
control.
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49. TYPES OF QUASI-EXPERIMENTAL
DESIGN
1. Nonrandomized control group design
2. Time-series design
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50. 1.Nonrandomized control group design
 It is also known as the ‘nonequivalent
control group design’.
 This design is identical to the pretest-posttest
control group design, except there is no random
assignment of subjects in experimental &
control groups.
 In this design, experimental & control groups are
selected without randomization, & dependent
variables are observed in experimental as well as
control groups before the intervention.
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51. • Later, the experimental group receives treatment
& after that posttest observation of dependent
variables is carried out for both the groups to
assess the effect of treatment on experiment
group
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52. Exp. group
Control group
Pretest
Pretest
Treatment Post-test
Post-test
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54. 2. Time-Series Design
Quasi-experimental approach involves time-
series data, in which researchers observe one
group of subjects repeatedly both before and
after the administration of the treatment.
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55. CON…
• This can be done in a controlled experimental
setting, but this design also lends itself well to
a more naturalistic setting in which data are
commonly collected on a group of subjects and
researchers are interested in the effects of some
treatment or intervention which they did not
experimentally apply.
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56. CON….
For example, researchers might examine the
yearly test scores of students at a given school
for several years both before and after the
implementation of an extended school day; in
this situation the yearly tests scores represent the
time-series data and the change to an extended
school day is the naturally occurring, quasi-
experimental treatment.
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57. CON….
This approach is an improvement over the single
pre-test/post-test design, which is unable to
demonstrate long-term effects.
The time-series data design can be further improved
by including a control group which is also examined
over time but which does not experience the
treatment; such a design is termed a multiple time-
series design.
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58. References
Burns, N. & Grove, S. K. (2007). Understanding
nursing research. (4th ed.).Philadelphia:W.B.
Saunders.
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