Experimental research in psychology allows researchers to test cause-and-effect relationships by manipulating independent variables and observing their impact on dependent variables. There are various types of experimental designs, including pre-experimental, true experimental, quasi-experimental, and single-subject designs. True experiments employ random assignment and control groups to establish internal validity and draw causal conclusions. Researchers must consider ethical standards to protect participants and ensure research is conducted properly.

1. Experimental Research
Presentation For
Psychology
Topic- Experimental Research in
Psychology

2. Experimental Research vs. Other Methods
❖ Can test for cause/effect relationships
❖ Manipulation of independent
variable(s)
Simply put:
Decisions about the forms and values of
the IV, as
well as about which group receives which
treatment
are at the sole discretion of the researcher
Tuesday,

3. Variables in Experimental Research
❖ Independent Variable:
❖ Experimental Variable, Cause, or Treatment
❖ The activity or characteristic the researcher believes
makes a difference
❖ Dependent Variable:
❖ Criterion Variable, Effect, or Posttest
❖ Outcome of the study
❖ Difference in group(s) that occurs as a result of the
manipulation of the IV
❖ Only constraint: must represent a measurable
outcome
Tuesday.

4. Characteristics of
Experimental Research
❖ Demanding & Productive, but...
❖ Produce the soundest evidence of
hypothesized cause-effect
relationships
❖ Difference between Correlational &
Experimental
Research:
❖ Correlational can be used to predict a
specific score for a
specific individual
❖ Experimental predicts more global
results

5. Steps in Experimental Research Study
1. Select and define problem.
2. Select subjects and [measurement]
instruments.
3. Select design.
4.Execute procedures.
5. Analyze data.
6.Formulate conclusions

6. Role of the Researcher
❖ Forms or selects groups
❖ Decides what will happen to each group
❖ Attempts to control all variables and factors
❖ Observes and measures effect on the groups
Every effort is made to make sure the 2 groups have
equivalent variables—except for the independent variable.
Tuesday,

7. Two Groups
❖ Experimental Group
❖ Receives the new treatment being investigated
❖ Control Group
❖ Receives a different treatment; or
❖ Receives same treatment as usual (i.e. is left
alone)
The Control Group is needed in order to
identify/measure any
differences observed as a result of the differing
treatments

8. Group Designs
❖ Two classes of experimental designs:
❖ Single-Variable: one independent variable; IV is
manipulated
❖ Three types—
❖ Pre-experimental
❖ True experimental*
❖ Quasi-experimental
❖ Factorial: two or more independent variables; at least one
IV
is manipulated
❖ Elaborate on single-variable designs;
❖ Investigates each variable independently and in
interaction
with other variables;
❖ Sky’s the limit

9. Pre-Experimental Designs
❖ One-Shot Case Study —
❖ One group exposed to one treatment then given posttest
❖ Don’t know level of group knowledge before the treatment!
❖ Sources of invalidity are not controlled!
❖ One-Group Pretest-Posttest Design —
❖ One group pretested, exposed to one treatment, then post tested
❖ Still a number of factors affecting validity that are not controlled!
❖ Other factors may influence any differences observed between the
pretest and posttest
❖ Static-Group Comparison —
❖ At least two groups; first receives new treatment; second receives
usual
treatment; both post tested
❖ Purpose of control group is to show how the experimental (first) group
would have performed had
they not received the new treatment
❖ Effective only to the degree that the two groups are equal to each
other

10. True Experimental Designs
❖ Pretest-Posttest Control Group Design —
❖ At least two randomly-assigned groups; both pretested for dependent variable;
one group then receives the new treatment; then both groups are post tested.
❖ Internal invalidity fully controlled by: random assignment, pretesting, & inclusion
of a control group
❖ Potential risk of interaction between the pretest and the treatment*
❖ Posttest-Only Control Group Design —
❖ Same as pretest-posttest design, except there is no pretest
❖ Subjects randomly assigned; exposed to independent variable; then post tested
❖ Mortality is not controlled for (no pretest), but may not be a problem anyway
❖ Solomon Four-Group Design —
❖ Random assignment of participants to one of four groups
❖ Two groups are pretested; two groups are not pretested
❖ One pretested group & one unpretested group receive the experimental treatment
❖ All four groups are post tested
❖ Combination of the two designs (above) - eliminates both sources of internal
invalidity!

11. Quasi-Experimental Designs
❖ Nonequivalent Control Group Design —
❖ Two or more existing groups pretested; administered treatment; and posttested.
❖ Participants’ assignment to groups is not random; assignment of treatments to
groups is random
❖ Invalidity sources include: regression, selection-treatment interactions (maturation,
history, and testing)
❖ Time-Series Design —
❖ One group repeatedly pretested; administered treatment; repeatedly posttested.
❖ Elaboration of the one-group pretest-posttest design; involves testing (pre- and
post-) more than once
❖ Advantage lies in confidence gained through significant improvement of group
scores between pretests and posttests
❖ Counterbalanced Designs —
❖ All groups received all treatments; each group receives treatment in a different
order than others.
❖ Any number of groups can be involved; limited only by the number of treatments;
# of groups = # of treatments
❖ Order of each groups’ receipt of treatment is determined randomly; each group is
posttested following each treatment
❖ Pretest usually not possible and/or feasible; often used on existing groups
❖ Weakness lies in potential for multiple-treatment interference; thus, should only be
used when this is not a concern

12. Factorial Designs
❖ Two or more independent variables; at least one is
manipulated by researcher
❖ Term “factorial” comes from the use of multiple
variables
with multiple levels
❖ 2 x 2 factorial design*
❖ Can get very complicated (2 x 3, 3 x 2, etc.)!
❖ Often employed after using a single-variable design;
❖ “Variables do not operate in isolation”
❖ Studies how variables behave at different levels**

13. Single-Subject Experimental Designs
❖ Also referred to as “single-case experimental designs”
❖ Used when sample size = 1; or for multiple individuals
considered as 1 group
❖ Variation of the time-series design
❖ Typically used as a study of behavioral change in an
individual
❖ Participant is own control; exposed to both non-
treatment &
treatment phases;
❖ Individual’s performance measured repeatedly during
all phases
❖ Non-treatment phase = A; Treatment phase = B

14. Validity in Single-Subject Experiments
❖ External Validity
❖ Frequent criticism due to lack of generalizability
❖ Can be counteracted through replication
❖ Internal Validity
❖ Repeated and Reliable Measurement
❖ If results are to be trusted, treatment must follow exact
same procedures every time
❖ Baseline Stability
❖ Provides basis for assessing the effectiveness of the
treatment; must do enough
baseline measurements to establish a pattern
❖ The Single Variable Rule
❖ Only one variable should be manipulated at any one time!

15. Types of Single-Subject Designs
❖ A-B-A Withdrawal Designs --
❖ The A-B* Design
❖ Establishment of baseline stability; treatment given
❖ Improvement during treatment = effectiveness of treatment
❖ The A-B-A Design
❖ Adds a second baseline measurement to the A-B design
❖ Improves validity IF behavior improves during the B phase, and
subsequently
deteriorates during the second A phase
❖ The A-B-A-B Design
❖ Adds a second treatment phase to the A-B-A design
❖ Could add strength to experiment IF behavior improves during
treatment twice!
❖ Eliminates ethical concerns from A-B-A design (ending with participant
not
receiving potentially effective treatment)

16. Types of Single-Subject Designs (cont’d)
❖ Multiple-Baseline Designs
❖ Alternative to the A-B design
❖ Used when unable to withdraw the treatment, or when it would be
unethical to do so
❖ Three basic types: across behaviors, across subjects, and across settings*
❖ Alternating Treatments Design
❖ Only valid design for assessing effectiveness of 2+ treatments in a single-
subject
context
❖ Rapid alternation of treatments for a single subject
❖ Treatments are alternated randomly
❖ Notice: no withdrawal phase, no baseline phase.
❖ Allows for the study of multiple treatments quickly and efficiently
❖ Could introduce multiple-treatment interference

17. Data Analysis/Interpretation
❖ Typically involves graphically-represented
results
❖ Design must be evaluated for adequacy;
then
treatment effectiveness is assessed
❖ Clinical Significance vs. Statistical
Significance
❖ t and F tests can be used to test for
statistical
significance

18. Infamous Cases of Unethical Research
❖ Tuskegee Syphilis Study (1932-1972)
❖ Nearly 400 African-American men were infected with syphilis
❖ Study conducted by Public Health Service
❖ Milgram Obedience to Authority Study (began 1961;
made public 1963)
❖ Residents of New Haven, CT recruited to participate in a study of
“memory and
learning”
❖ Participants asked to inflict electric shocks in increasing voltages
based on
“learner’s” incorrect answers (maximum voltage of 450 volts)
❖ Stanford Prison Experiment (1971)
❖ 24 students chosen as “prisoners,” while 9 “guards” were assigned to
3 shifts
❖ Shut down after 6 days (originally intended to take 2 weeks) due to a
deterioration of the experiment’s conditions and structure

19. THANK YOU
Presentation By:-
Ujjwala Gaur
(B.A. 5th Semester)