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EXPERIMENTAL RESEARCH DESIGNS
CHAPTER-4
What is an Experiment?
An experiment is generally used to
infer a causality. In an experiment, a
researcher actively manipulates one
or more causal variables and
measures their effects on the
dependent variable of interest.
SLIDE 4-1
Necessary Conditions for Making
Causal Inferences
Concomitant variation
Time order of occurrence of variables
Absence of other possible causal factors
SLIDE 4-2
Concepts Used in Experiments
Independent variables: Independent variables
are also known as explanatory variables or
treatments. The levels of these variables are
manipulated (changed) by researchers to
measure their effect on the dependent variable.
Test units: Test units are those entities on which
treatments are applied.
Dependent variables: These variables measures
the effect of treatments (independent variable) on
the test units.
SLIDE 4-3
Concepts Used In Experiments
Experiment: An experiment is executed when the
researcher manipulates one or more independent
variables and measures their effect on the dependent
variables while controlling the effect of the
extraneous variables.
Extraneous variables: These are the variables other
than the independent variables which influence the
response of test units to treatments.
Examples: Store size, government policies,
temperature, food intake, geographical location, etc.
SLIDE 4-4
Validity in Experimentation
Internal validity: Internal validity tries to examine
whether the observed effect on a dependent
variable is actually caused by the treatments
(independent variables) in question.
External validity: External validity refers to the
generalization of the results of an experiment.
The concern is whether the result of an
experiment can be generalized beyond the
experimental situations.
SLIDE 4-5
Factors Affecting Internal Validity
of the Experiment
History
Maturation
Testing
Instrumentation
Statistical regression
Selection bias
Test unit mortality
SLIDE 4-6
Factors Affecting External Validity
The environment at the time of test may be
different from the environment of the real world
where these results are to be generalized.
Population used for experimentation of the test
may not be similar to the population where the
results of the experiments are to be applied.
Results obtained in a 5–6 week test may not hold
in an application of 12 months.
Treatment at the time of the test may be different
from the treatment of the real world.
SLIDE 4-7
Methods to Control Extraneous
Variables
Randomization
Matching
Use of experimental designs
Statistical control
SLIDE 4-8
Environments of Conducting
Experiments
Laboratory Environment - In a laboratory
experiment, the researcher conducts the
experiment in an artificial environment
constructed exclusively for the experiment.
Field Environment - The field experiment is
conducted in actual market conditions. There is
no attempt to change the real-life nature of the
environment.
SLIDE 4-9
A Classification of Experimental
Designs
SLIDE 4-10
Pre-experimental design
Pre-experimental designs do not make use of any randomization
procedures to control the extraneous variables. Therefore, the
internal validity of such designs is questionable.
One-shot case study:
X O
One-group pre-test–post-test design:
O1 X O2
Static group comparison:
Group 1 - X O1
Group 2 - O2
SLIDE 4-11
Quasi-experimental designs
In quasi-experimental design, the researcher can
control when measurements are taken and on
whom they are taken. However, this design lacks
complete control of scheduling of treatment and
also lacks the ability to randomize test units’
exposure to treatments.
Time series design:
O1 O2 O3 O4 X O5 O6 O7 O8
Contd…..
SLIDE 4-12
Quasi-experimental designs
SLIDE 4-13
Quasi-experimental designs
Multiple time series design:
Experimental Group: O1 O2 O3 O4 X O5 O6 O7 O8
Control Group: O′1 O′2 O′3 O′4 O′5 O′6 O′7 O′8
SLIDE 4-14
True experimental designs
In true experimental designs, researchers can
randomly assign test units and treatments to an
experimental group. Here, the researcher is able to
eliminate the effect of extraneous variables from
both the experimental and control group.
Pre-test–post-test control group:
Experimental Group: R O1 X O2
Control Group: R O3 O4
SLIDE 4-15
True experimental designs
Post-test – only control group design:
Experimental Group: R X O1
Control Group: R O2
Solomon four-group design:
Experimental Group 1 : R O1 X O2
Control Group 1: R O3 O4
Experimental Group 2: R X O5
Control Group 2: R O6
SLIDE 4-16
Statistical designs
Statistical designs allow for statistical control and
analysis of external variables.
Completely randomized design
Randomized block design
Latin square design
Factorial design
SLIDE 4-17
END OF CHAPTER

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Ch.4 ppt

  • 2. What is an Experiment? An experiment is generally used to infer a causality. In an experiment, a researcher actively manipulates one or more causal variables and measures their effects on the dependent variable of interest. SLIDE 4-1
  • 3. Necessary Conditions for Making Causal Inferences Concomitant variation Time order of occurrence of variables Absence of other possible causal factors SLIDE 4-2
  • 4. Concepts Used in Experiments Independent variables: Independent variables are also known as explanatory variables or treatments. The levels of these variables are manipulated (changed) by researchers to measure their effect on the dependent variable. Test units: Test units are those entities on which treatments are applied. Dependent variables: These variables measures the effect of treatments (independent variable) on the test units. SLIDE 4-3
  • 5. Concepts Used In Experiments Experiment: An experiment is executed when the researcher manipulates one or more independent variables and measures their effect on the dependent variables while controlling the effect of the extraneous variables. Extraneous variables: These are the variables other than the independent variables which influence the response of test units to treatments. Examples: Store size, government policies, temperature, food intake, geographical location, etc. SLIDE 4-4
  • 6. Validity in Experimentation Internal validity: Internal validity tries to examine whether the observed effect on a dependent variable is actually caused by the treatments (independent variables) in question. External validity: External validity refers to the generalization of the results of an experiment. The concern is whether the result of an experiment can be generalized beyond the experimental situations. SLIDE 4-5
  • 7. Factors Affecting Internal Validity of the Experiment History Maturation Testing Instrumentation Statistical regression Selection bias Test unit mortality SLIDE 4-6
  • 8. Factors Affecting External Validity The environment at the time of test may be different from the environment of the real world where these results are to be generalized. Population used for experimentation of the test may not be similar to the population where the results of the experiments are to be applied. Results obtained in a 5–6 week test may not hold in an application of 12 months. Treatment at the time of the test may be different from the treatment of the real world. SLIDE 4-7
  • 9. Methods to Control Extraneous Variables Randomization Matching Use of experimental designs Statistical control SLIDE 4-8
  • 10. Environments of Conducting Experiments Laboratory Environment - In a laboratory experiment, the researcher conducts the experiment in an artificial environment constructed exclusively for the experiment. Field Environment - The field experiment is conducted in actual market conditions. There is no attempt to change the real-life nature of the environment. SLIDE 4-9
  • 11. A Classification of Experimental Designs SLIDE 4-10
  • 12. Pre-experimental design Pre-experimental designs do not make use of any randomization procedures to control the extraneous variables. Therefore, the internal validity of such designs is questionable. One-shot case study: X O One-group pre-test–post-test design: O1 X O2 Static group comparison: Group 1 - X O1 Group 2 - O2 SLIDE 4-11
  • 13. Quasi-experimental designs In quasi-experimental design, the researcher can control when measurements are taken and on whom they are taken. However, this design lacks complete control of scheduling of treatment and also lacks the ability to randomize test units’ exposure to treatments. Time series design: O1 O2 O3 O4 X O5 O6 O7 O8 Contd….. SLIDE 4-12
  • 15. Quasi-experimental designs Multiple time series design: Experimental Group: O1 O2 O3 O4 X O5 O6 O7 O8 Control Group: O′1 O′2 O′3 O′4 O′5 O′6 O′7 O′8 SLIDE 4-14
  • 16. True experimental designs In true experimental designs, researchers can randomly assign test units and treatments to an experimental group. Here, the researcher is able to eliminate the effect of extraneous variables from both the experimental and control group. Pre-test–post-test control group: Experimental Group: R O1 X O2 Control Group: R O3 O4 SLIDE 4-15
  • 17. True experimental designs Post-test – only control group design: Experimental Group: R X O1 Control Group: R O2 Solomon four-group design: Experimental Group 1 : R O1 X O2 Control Group 1: R O3 O4 Experimental Group 2: R X O5 Control Group 2: R O6 SLIDE 4-16
  • 18. Statistical designs Statistical designs allow for statistical control and analysis of external variables. Completely randomized design Randomized block design Latin square design Factorial design SLIDE 4-17