Moderation

This week is about using regression for testing moderation hypotheses as well as curvilinear hypotheses.

Primary readings

Kenny, David. Handout on moderation [html]
UCLA handout on curvilinear relationships [html]
Spiller, S. A., Fitzsimons, G. J., Lynch Jr, J. G., & McClelland, G. H. (2013). Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression. Journal of Marketing Research, 50(2), 277-288. [pdf]
- Ajay Mehra, Martin Kilduff and Daniel J. Brass. The Social Networks of High and Low Self-Monitors: Implications for Workplace Performance. Administrative Science Quarterly. Vol. 46, No. 1 (Mar., 2001), pp. 121-146
- [pdf]

Secondary readings

Kromrey, J. D., & Foster-Johnson, L. (1998). Mean centering in moderated multiple regression: Much ado about nothing. Educational and Psychological Measurement, 58(1), 42-67. [^pdf]
Sutton, R.I. and A. Rafaeli. 1988. "Untangling the relationship between displayed emotions and organizational sales: The case of convenience stores." Academy of Management Journal. 31(3):461-487. [^pdf]
- in my view, the effect of smiles on sales is moderated by linelength
Phil Ender handout

Slides

Do files for today

Datasets and Stata Do files

Protest dataset
- - includes do file for creating interaction plots and for Neyman-Johnson floodlighting
GSS2008 dataset
- - includes do file for creating interaction plots and for Neyman-Johnson floodlighting
  - includes do file for testing curvilinear relations

Software tools for SPSS

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]
After installing PROCESS, we will be working with the gss2008 dataset. A few commands we will execute:

- compute revhappy = 4 - happy
  - filter the cases to retain only sibs < 20 and income > 0 and income < 13
- process vars=sex age sibs income childs revhappy/y=revhappy/x=childs/m=income/model=1/jn=1/quantile=1/plot=1.

Old Slides