Types of Variables > Moderating Variable
What is a Moderating Variable?A moderating variable, also called a moderator variable or simply M, changes the strength or direction of an effect between two variables x and y. In other words, it affects the relationship between the independent variable or predictor variable and a dependent variable or criterion variable. Moderating variables can be qualitative (non-numerical values like race, socioeconomic class or sex) or quantitative (numerical values like weight, reward level or age). For example:
- According to the American Psychological Association, stress has a bigger impact on men than women. Sex is a qualitative variable that moderates the strength of an effect between stress and health status.
- There may be a relationship between socioeconomic status and how often women perform self-exams on their breasts. Age is possibly a numerical moderating variable: the relationship for socioeconomic status and breast self-exams might be weaker in younger women and stronger in older women.
In correlation studies, the moderating variable is defined as a third variable — z — that affects the correlation between two variables x and y. A statistically significant moderating variable can amplify or weaken the correlation between x and y.
Finding the Variables
The moderating variable is technically another predictor variable, so you would run multiple regression analysis (called moderator analysis by some software) to find the moderating variables.
In SPSS: Laerd.com has thorough steps for the analysis, with step by step images.
In Stata: the process is a little lengthy, but you can find a guideline on the UCLA website.
American Psychological Association (undated). Stress and Gender. Retrieved May 12, 2016 from here.
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, 1173-1182.
Hayes, A.F. (2013) Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: Guilford Press
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