Mediation

This week's class focuses on using regression to test mediation. More generally, we discuss the issue of controlling for alternative effects and spurious relationships. In this context you might find the hemline index and the Superbowl hypothesis interesting.

Primary Readings

• Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis. New York: The Guilford Press. Chapter 1 [pdf]

  • Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173. [pdf]

    • Kenny handout on testing mediation. [html]

• Zhao, Lynch, and Chen (JCR 2010) -- Reconsidering Baron and Kenny: Myths and Truths About Mediation Analysis [^pdf]

• Handout on using process [html]

Secondary Readings

• Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891

• Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408-420

• Simpson's paradox (aka ecological fallacy)

Software tools

• PROCESS macro for SPSS and SAS

  • • Download latest from http://www.processmacro.org or use this (possibly old) zip file (zip)

    • Documentation:

      • Brief handout [html]

    • Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis. New York: The Guilford Press. [web page] This is a really useful book.

• • See also this article:

    • Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717-731. [pdf]

  • Equivalent code for STATA

  • DeRosia

Stata Do Files

• Mediation files

Datasets

• Neogen

• GSS 2008

PROCESS commands

• • Open GSS dataset

    • process vars= prestg80 rtheism rself/y=prestg80/x=rtheism/m=rself/model=4/total=1/effsize=1/boot=10000/normal=1.

    • process vars= sex childs polviews prestg80/y=polviews/x=sex/m=prestg80 childs/model=4/total=1/effsize=1/boot=10000/normal=1

  • Open Neogen dataset

    • create perf and iadvice variables from longer-named originals

    • process vars= perf iadvice knowjob/y=perf/x=iadvice/m=knowjob/model=4/total=1/effsize=1/boot=10000/normal=1