I intend to run a sequential mediation for a study but am at a lost as to my data. My search shows process macro is not for panel data, but my data is panel. can i be assisted in running a mediation analysis for my panel data?
Will there be the need for justifying why Re or FE in running mediation with panel data?
I have used Process Macro for the mediation analysis and included year fixed effect (year dummies) and industry fixed effect (industry dummies). But i am struggling in justifying why fixed effect.
Yes I will send some papers to you. But please, can you explain the nature of your data it will help in selecting techniques and tools of analysis. You can easily conduct the pre estimation test to meet OLS assumptions (normality, multicolinearity, hetro and Hausman tests using Stata. These are possible in the sequence of regressions to meet the conditions of mediation in line with Baron and Kenny (1986) and Hayes et al. (2013).
I have done the mediation with process marco by Hayes in SPSS. My concern is justifying which panel model. FE or RE or Pooled.
If i test my individual relationship i can run panel (Fe, RE or pooled) and use the necessary tests to make the right choice (Hausman).
But in process macro there is nothing like FE, RE. is a pooled regression. Assuming my earlier test indicates i use RE. Then hoe w do i do that when running mediation. Or test says FE is better how do i run FE mediation. i will appreciate tour response
OK, I understand, I think running fixed or random effects in mediation model can be done in the last sequence of mediation. That's when you run the dv and ivs while controlling for mediator. But actually I'm an expert in process macro. We wait for experts in spss to response.
Ummi Junaidda Hashim , Hussaini Bala here is the example for cross-sectional data: https://data.library.virginia.edu/introduction-to-mediation-analysis/?fbclid=IwAR1xUaMSnTqBAXmrBCKDMTZnc41c7CaVJ-bF3MYMqXV7CWhSs4cqk46-KOk
It's in R. Package mediation works not just with cross-sectional data. You can perform mediation analysis, using package lme4, which is for multi-level data. You can elaborate regression models using lme4 and perform mediation analysis via function mediate.
You can see the difference between usual fixed and random effects models and multi-level data regressions here: https://stackoverflow.com/questions/49033016/plm-or-lme4-for-random-and-fixed-effects-model-on-panel-data