14-1

14-2McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc.,All Rights

Reserved.

Part ThreeSOURCES AND

COLLECTION OF DATA

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Chapter FourteenEXPERIMENTATION

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Variables in Experiments

• Independent variables

• Dependent variables

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Advantages of an Experiment?

• Researcher’s ability to manipulate the independent variable

• Contamination from extraneous variables can be controlled more efficiently

• Convenience • Cost• Replication

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Disadvantages of Experiments

• Artificiality of the laboratory

• Generalization from nonprobability samples

• Larger budgets needed

• Restricted to problems of the present or immediate future

• Ethical limits to manipulation of people

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Experimentation Process

• Select relevant variables

• Specify the treatment levels

• Control the experimental environment

• Choose the experimental design

• Select and assign the participants

• Pilot-test, revise, and test

• Analyze the data

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Ways to Assign Subjects

• Random Assignment

• Matching Assignment– Quota matrix

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Does a Measure Accomplish What it Claims?

• Internal validity

• External validity

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Threats to Internal Validity

• History

• Maturation

• Testing

• Instrumentation

• Selection

• Statistical Regression

• Experimental Mortality

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Threats to External Validity

• The Reactivity of Testing on X

• Interaction of Selection and X

• Other Biasing Effects on X – Artificial setting of testing– Respondents knowledge of testing

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Experimental Designs

• Preexperimental designs

• True experimental designs

• Field experiments

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Design Symbols

X the introduction of an experimental stimulus to the participant

0 a measure or observation activity

R an indication that sample units have been randomly assigned

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Preexperimental Designs

• One-shot case study

• One-group pretest-posttest design

• Static group comparison

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True Experimental Designs

• Pretest-posttest control group design

• Posttest-only control group design

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Operational Extensions of True Designs

• Completely randomized designs

• Randomized block design

• Latin square

• Factorial design

• Covariance analysis

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Field Experiments: Quasi- or Semi-Experiments

• Non Equivalent Control Group Design

• Separate Sample Pretest-Posttest Design

• Group Time Series Design