EXPERIMENTAL DESIGNS- TYPES AND THEIR ANALYSIS TECHNIQUES

1. RESEARCH
METHODOLOGY
EXPERIMENTAL DESIGNS- TYPES AND THEIR
ANALYSIS TECHNIQUES
NIVEDITA MENON. C
06/03/2021

2. EXPERIMENTAL DESIGNS
 Experimental design means creating a set of procedures to test a
hypothesis.
 A good experimental design requires a strong understanding of
the system you are studying.
• By first considering the variables and how they are related (Step
1),
• you can make predictions that are specific and testable (Step 2).

3. • How widely and finely you vary your independent variable (Step
3) will determine the level of detail and the external validity of
your results.
• Your decisions about randomization, experimental controls, and
independent vs repeated-measures designs (Step 4) will
determine the internal validity of your experiment.

4. TYPES OF DESIGNS
True Experiments
Quasi- Experimental Designs
Pre Experimental Designs
Ex Post Facto Designs

5. TRUE EXPERIMENTS
 In general, designs considered to be true experiments contain
three basic key features:
1. random assignment of participants into experimental and
control groups
2. a treatment (or intervention) provided to the experimental
group
3. measurement of the effects of the treatment in a post-test
administered to both groups.
 Some true experiments are more complex. Their designs can also
include a pre-test and can have more than two groups, but these
are the minimum requirements for a design to be a true
experiment.

6. 1. Experimental and Control Groups
 the effect of an intervention is tested by comparing two groups:
• one that is exposed to the intervention; the experimental group,
also known as the treatment group and
• another that does not receive the intervention; the control group.
 Importantly, participants in a true experiment need to be
randomly assigned to either the control or experimental groups.
2. Treatment or Intervention
 In an experiment, the independent variable is receiving the
intervention being tested.
 In some cases, it may be immoral to withhold treatment
completely from a control group within an experiment.

7.  For these cases, researchers use a control group that receives “treatment
as usual”. Experimenters must clearly define what treatment as usual
means.
 A substance abuse researcher conducting an experiment may use
twelve-step programs in their control group and use their experimental
intervention in the experimental group.
 The results would show whether the experimental intervention worked
better than normal treatment, which is useful information.
3. Post-Test
 The dependent variable is usually the intended effect the researcher
wants the intervention to have.
 Thus, the researcher must at a minimum, measure the number of
episodes that occur after the intervention, which is the post-test.
 In a classic experimental design, participants are also given a pretest to
measure the dependent variable before the experimental treatment
begins.

8. QUASI-EXPERIMENTAL DESIGNS
 Quasi-experimental designs are similar to true experiments, but
they lack random assignment to experimental and control groups.
 Quasi-experimental designs have a comparison group that is
similar to a control group except assignment to the comparison
group is not determined by random assignment.
 While this method is more convenient for real-world research, it
is less likely that that the groups are comparable than if they had
been determined by random assignment.

9.  Quasi-experiments are particularly useful in social welfare policy
research.
 Non equivalent comparison group design are as follows:
1. Natural Experiments
 Social welfare policy researchers often look for what are termed
natural experiments or situations in which comparable groups are
created by differences that already occur in the real world.
 Natural experiments are a feature of the social world that allows
researchers to use the logic of experimental design to investigate
the connection between variables.
2. Matching
 It begins with researchers thinking about what variables are
important in their study, particularly demographic variables or
attributes that might impact their dependent variable.

10. • Individual matching involves pairing participants with similar
attributes.
• Then, the matched pair is split—with one participant going to the
experimental group and the other to the comparison group.
• Researchers may engage in aggregate matching, in which the
comparison group is determined to be similar on important variables.
1. The Time Series Design
 The time series design uses multiple observations before and after an
intervention.
 In some cases, experimental and comparison groups are used. In other
cases where that is not feasible, a single experimental group is used.
 By using multiple observations before and after the intervention, the
researcher can better understand the true value of the dependent
variable in each participant before the intervention starts.
 Additionally, multiple observations afterwards allow the researcher to
see whether the intervention had lasting effects on participants.

11. PRE-EXPERIMENTAL DESIGN
 Pre-experimental designs are called such because they often
happen as a pre-cursor to conducting a true experiment.
 Researchers want to see if their interventions will have some
effect on a small group of people before they seek funding and
dedicate time to conduct a true experiment.
 Pre-experimental designs, thus, are usually conducted as a first
step towards establishing the evidence for or against an
intervention.
1. One-group Pre-test Post-test Design
 Pre- and post- tests are both administered, but there is no
comparison group to which to compare the experimental group.

12.  Researchers may be able to make the claim that participants
receiving the treatment experienced a change in the dependent
variable, but they cannot begin to claim that the change was the
result of the treatment without a comparison group.

13. EX POST FACTO RESEARCH DESIGN
 An ex post facto research design is a method in which groups
with qualities that already exist are compared on some dependent
variable.
 Also known as "after the fact" research, an ex post facto design is
often considered quasi-experimental because the subjects are not
randomly assigned - they are grouped based on a particular
characteristic or trait.
 Although differing groups are analyzed and compared in regards
to independent and dependent variables it is not a true experiment
because it lacks random assignment. The assignment of subjects
to different groups is based on whichever variable is of interest to
the researchers.