Hi everyone, I'm using PROCESS model 1 to explore the direct effect of continuous variable X and the moderation effect of continuous variable W on the association between continuous X and Y. However, the data didn't meet with the assumption of normal distribution. Should I continue to carry out the model or replace it with other methods?
Hello Bette Jingyi Wu. How exactly did you assess the "normality" assumption? Thanks for clarifying.
Do you mean mediation or moderation?!
If you mean mediation, you can use generalized structural equation modeling (GSEM) in Stata.
If you mean moderation, you can conduct continuous or categorical interaction.
The PROCESS macro can handle non-normal data and assess moderation effects without relying on strict assumptions of normality. You could refer to Hayes’s (2022) book, referenced below, for insights.
Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). The Guilford Press. https://www.guilford.com/books/Introduction-to-Mediation-Moderation-and-Conditional-Process-Analysis/Andrew-Hayes/9781462549030
Good luck,
The bias-corrected bootstrap confidence intervals were used to control for the possibility of the non-normal distribution of sampling.
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