Message/Author 

Jo Brown posted on Wednesday, May 16, 2012  4:47 am



Hi There, I am exploring a simple mediation model and would like to adjust it for confounders (z1  z5) which I believe may influence the c path (X> Y). I am not sure where/how to specify them. Should they be included in all regressions statements or just the Y on X one (as below)? Should they also be specified in the MODEL INDIRECT command as well? Model: Y on m ; Y on X z1 z2 z3 z4 z5; m on X; MODEL INDIRECT: Y IND X; Thanks 

Emil Coman posted on Wednesday, May 16, 2012  11:11 am



I would try to take a stab at this, if I may: Judd & Kenny (2009) list this as the most problematic assumption, that m and Y have no common causes (p. 117), so you are doing what few researcher do (great!). In your case, it seems you want to add : m on z1 z2 z3 z4 z5; And the INDIRECT command should be fine, just make it Y IND m X; INDIRECT is going to estimate the effect flowing from X through m, which will not go through the confounders too. Judd, C., & Kenny, D. (2009). Data Analysis in Social Psychology: Recent and Recurring Issues. In S. T. Fiske, D. T. Gilbert & G. Lindzey (Eds.), Handbook of Social Psychology, Volume One (pp. 113137). Hoboken, NJ: Wiley. Cheers, emil 


I would also include the confounders in the m regression: m on X z1 z2 z3 z4 z5; There is no need to change the IND statement. 

Jo Brown posted on Thursday, May 17, 2012  5:10 am



Thanks for your replies. Just to doublecheck my model should be: Model: Y on m ; Y on X z1 z2 z3 z4 z5; m on X z1 z2 z3 z4 z5; MODEL INDIRECT: Y IND X; Jo 


This is correct. 

Jo Brown posted on Friday, May 18, 2012  7:32 am



Thanks again! 

Jo Brown posted on Wednesday, May 23, 2012  4:06 am



Hi Linda, I set the model as you suggested: Model: Y on m ; Y on X z1 z2 z3 z4 z5; m on X z1 z2 z3 z4 z5; MODEL INDIRECT: Y IND X; and asked standardised estimates using output: sampstat; However, the output for the indirect and direct effect produces estimates of .00 and does not show p value unless I specify the bootstrap option; does this seem reasonable? Jo 


Please send the output and your license number to support@statmodel.com. 


Hi Linda, could you direct me towards a paper/website which explain the difference between using the two mediation commands below and what is the rational for using one over the other: Model: Y on m ; Y on X z1 z2 z3 z4 z5; m on X; and Model: Y on m ; Y on X z1 z2 z3 z4 z5; m on X z1 z2 z3 z4 z5; 


I would use the second case to avoid leaving out an important predictor of m. 

Joseph posted on Monday, June 10, 2013  12:57 pm



Dear Linda, I have a mediation model with measures collected at 3 time points: x1>m2>y3. I recently read the paper by Cole & Maxwell (2003) who suggest that to adjust a mediation model it is necessary to adjust path a for the mediator at baseline (i.e. time 1) to capture the actual change. I am not sure whether it is sufficient to do so or whether I should also adjust the other paths with m1 so that y on x m1 m2; m2 on x m2; Do you have any views on this? thanks! 


This is a good, general question for SEMNET. 

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