**Measuring and Manipulating Variables:**

**Reliability and Construct Validity**

I. Overview

II. Measurement

A. Where observers can go wrong

1. Observer bias2. Random observer error

B. Minimizing observer error

1. Reducing observer bias2. Reducing random observer error

C. Errors in administering the measure

D. Errors due to the participant

1. Random error2. Subject bias

a. Social desirability biasb. Obeying demand characteristics

3. Reducing subject bias

E. Reliability

1. Assessing overall reliability2. Assessing observer reliability

3. Assessing random error due to participants

4. Conclusions about reliability

F. Beyond reliability: Construct validity

1. Discriminant validation strategies: Showing that you aren't measuring the wrong construct2. Convergent validation strategies: Showing that you are measuring the right construct

3. Content validity: Is everything represented?

4. Summary of construct validity

III. Manipulating Variables

A. Common threats to a manipulation's validity

1. Random error2. Researcher bias

3. Subject biases

B. Evidence used to argue for validity

1. Consistency with theory2. Manipulation checks

C. Tradeoffs among three common types of manipulations

1. Instructional manipulations2. Environmental manipulations

3. Manipulations involving stooges

D. Manipulating variables: A summary

VI. Concluding remarks

Summary

Exercises

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