Experimental andQuasi-ExperimentalResearch

Experimental andQuasi-ExperimentalResearch

CHAPTER CHAPTER 7

Chapter Outline

• Sources of invalidity

• Threats to internal validity

• Threats to external validity

• Controlling threats to internal validity

• Controlling threats to external validity

• Types of designs

Experimental Research Tries to Establish Cause and Effect

• Selection of a good theoretical framework

• Application of appropriate experimental design

• Use of correct statistical model and analysis

• Proper selection and control of independentvariables

• Appropriate selection and measurement ofdependent variables

• Correct interpretation of results

Three Criteria for Causeand Effect

1. The cause must precede the effect in time.

2. The cause and effect must be correlated witheach other.

3. The correlation between cause and effect cannotbe explained by another variable.

If the condition is necessary and sufficient to produce the effect, then it is the cause.

Distinguishing Between Types of Validity

• Internal validity: Did the treatments (IV) causethe change in the outcome (dv)?

• Is there a trade-off between internal and externalvalidity?

• External validity: To what populations, settings, or treatments can the outcome be generalized?

• Can a series of studies address the trade-off?

Threats to Internal Validity

• History: Events that are not part of treatment

• Maturation: Events due to passage of time

• Testing: Effects of more than one test administration

• Instrumentation: Change in calibration ofmeasurements

• Statistical regression: Selection based on extreme score

(continued)

Threats to Internal Validity

• Selection biases: Nonrandom participantselection

• Experimental mortality: Differential loss of participants

• Selection–maturation interaction: Passage of time influencing groups differently

• Expectancy: Influence of experimenters onparticipants

Threats to External Validity

• Reactive or interactive effects of testing: Pretestmay make participants sensitive to treatment.

• Reactive effects of experimental arrangements:Setting constraints may influence generalizability.

• Multiple-treatment interference: One treatmentmay influence the next treatment.

Controlling Threats to Internal Validity

• Randomization

• Placebos

- Real randomization- Matched pairs (not matched groups)- Randomizing treatments or counterbalancing

• Blind setups

(continued)

Controlling Threats to Internal Validity

• Double-blind setups

• Reactive effects of testing: Eliminate pretest.

• Instrumentation

• Experimental mortality: Keeping participants

- Calibration and test reliability- Halo effects

Controlling Threats to External Validity

• Selecting from larger populations

• Ecological validity: Does the setting capture theessence of the real world?

- Participants- Treatments- Situations

Types of Designs: Preexperimental Designs

One-shot studies

T O

One-group pretest-posttest

O1 T O2 Statistical analysis?

Static group comparison

T O1

------------- Statistical analysis?

O2

Types of Designs: True Experimental Designs

Randomized-groups design

R T O1 Statistical analysis?R O2

Extending the levels—randomized-groups design

R T1 O1

R T2 O2 Statistical analysis?R O3

(continued)

Types of Designs: True Experimental Designs

(continued)

Types of Designs: True Experimental Designs

Pretest-posttest randomized-groups

R O1 T O2

R O3 O4 Statistical analysis?

(continued)

Extending the design on the RM factor

R O1 T O2 T O3 Statistical analysis? RO4 O5 O6

Types of Designs: True Experimental Designs

Solomon four-group design—purpose

R O1 T O2

R O3 O4

R T O5

R O6

Statistical analysis (factorial ANOVA)

No treatment TreatmentPretested O4 O2

Unpretested O6 O5

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Quasi-Experimental Designs: Time Series

Campbell and Stanley 1963.

Quasi-Experimental Designs: Reversal

Quasi-Experimental Designs: Ex Post Facto

This is one of the preexperimental designs, but withthe treatment not under the control of the experimenter.

T O1

----------------------- Statistical analysis?O2

Quasi-Experimental Designs:Single Participant

Identify participant and follow over time.

• Does the treatment produce the same effecteach time?

• Are treatment effects cumulative, or does participant return to baseline?

• Does participant’s response become less variableover treatment times?

(continued)

Quasi-Experimental Designs:Single Participant

• Is participant’s magnitude of response sensitiveto multiple treatment applications?

• Do varying intensities, frequencies, and lengthsof treatment produce varying responses?