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Psychology 242
Research in Psychology
Dr. David J. McKirnan


Week14 & 15
Multivariate and within-subjects designs.

Lecture notes

So far we have been talking about simple designs that assign subjects to one group or the other (i.e., control or experimental) . These are between-subjects designs. We will discuss different conditions when it is more informative for subjects to be in more than one condition, or to be measured more than once: "within subject" designs.

Understand the key features of these designs:

Lecture notes are here.

Readings

Your Chapter on Within-Subjects and Matched Subjects Approaches (Chapter 10 in Ray) & discussion of interpreting studies with multiple measured and unmeasured variables, and readings on interpreting “relative risk” statistics, and interpreting data about risks + benefits of mammography.

Discussion group Assignment

 

Develop a multivariate design

This week you will turn your study into a factorial or randomized block design. Take a look at the lecture notes for examples of multivariate studies.  Model your study on one of these designs if that helps, but think of something original.

  1. Take your paper topic and reframe it as having two (or more) Independent Variables.  You already specified one IV for your paper.  Now think of another IV; you could add
    • A true Independent variable – a second manipulation, in a factorial design;
    • A blocking variable, such as a status variable (age group, gender, ethnicity...); or
    • A within-subject variable, where you follow participants over time or have participants in > 1 experimental condition (e.g., each participant gets both the experimental and control condition).
  2. Write the main effect hypotheses. There will be one for each independent variable.
    • You already have written a hypothesis for your study IV.
    • Now write main effect hypotheses for the variable(s) you are adding..
  3. Write the interaction hypothesis.
    • Does one variable have an effect on the Dependent Variable only at one level of the other IV?
    • Does one variable have opposite effects on the DV at each level of the second IV?
  4. Sketch out a graph that illustrates data that would support the interaction hypothesis.
  5. What do you know by testing the two (or more) variables together that you might not have detected by testing one at a time?

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