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Understanding Internal Validity and Experimental Design in Psychology Research

This lecture review delves into key concepts of internal validity in psychological research, addressing threats such as nonequivalent control groups, history, and maturation. It also covers operational definitions, including how to operationalize independent and dependent variables in various studies on racial attitudes, word length effects, and cognitive therapy impacts. Additionally, the importance of Type I and Type II errors is discussed, alongside the advantages of multi-level and factorial designs for efficient experimental outcomes, highlighting the significance of interactions and main effects in analyzing data.

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Understanding Internal Validity and Experimental Design in Psychology Research

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  1. Lecture 14Psyc 300A

  2. Review • Operational definitions • Internal validity • Threats to internal validity • Type I and type II errors

  3. Review: Operational definitions • For each of these studies, operationalize the IV and DV: • The effect of exposure to other racial groups on prejudicial attitudes • The effect of word length on speed of reading • The effect of cognitive therapy on depression

  4. Review: Internal validity • What is internal validity? • Ability to make valid inferences concerning the relationship between the IV and DV in an experiment. (effect on the DV is caused only by the IV) • The extent to which the results of an experiment can be attributed t the manipulation of the IV rather than to some confounding variable

  5. Review: Threats to Internal Validity • Nonequivalent control group • History • Maturation • Testing • Regression to the mean • Instrumentation • Mortality/Attrition

  6. Type I and Type II Errors

  7. Power • Power is the probability of avoiding a Type II error. (Finding an effect if there really is one there to find) • Power is related to: • Alpha level • Effect size (mean and sd) • Number of participants

  8. Review: Advantages of Multi-level Designs • What is a multi-level design? • Advantages: • Efficiency (fewer participants needed and less time) • Ability to see relationships better

  9. Review: Multifactor Designs • Factorial design: A design in which all levels of each IV are combined with all levels of the other IVs. • Advantages of factorial designs: • More efficient (fewer participants and less experimenter time) • Allows us to see how variables interact, see complex relationships

  10. Example: Movie Preferences

  11. What a Factorial Design Tells You • Main effect: The effect of an IV on the DV, ignoring all other factors in the study. (Compare means of different levels of IV, while ignoring [collapsing across] other IVs [ i.e., compare marginal means]) • Interaction effect: When the effect of one IV on a DV differs depending on the level of a second IV. • Interpret the interaction first

  12. Examples of Main Effects and Interactions • A1= morning • A2= late afternoon • B1= high fat diet • B2= low fat diet • DV: 0-50 rating of energy level

  13. More Main Effects and Interactions • A1= morning • A2= late afternoon • B1= high fat diet • B2= low fat diet • DV: 0-50 rating of energy level

  14. More Main Effects and Interactions • A1= morning • A2= late afternoon • B1= high fat diet • B2= low fat diet • DV: 0-50 rating of energy level

  15. Group Exercise: Main Effects and Interactions • Any questions from p.205 in book?

  16. Example: Psychotherapy Outcome

  17. Group Activity: Main Effects and Interactions Make graphs of the following situations:

  18. Factorial Designs: Naming Conventions • The first number is the number of levels in first IV, second number is number of levels in second IV, etc. • 2 x 2 • 2 x 3 • 2 x 2 x 3 • Between-subjects, repeated measures (within), mixed

  19. A 2 x 3 Interaction

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