Question on Model selection for data mediation effect analysis

[vivian fang]

Code	X(Treated or Controlled)	Time1		Time2
M1	Y1	M2	Y2
1	0	...	...	...	...
2	1	...	...	...	...
3	0	...	...	...	...
4	1	...	...	...	...

My data is formatted as shown in the figure, consisting of individual data with two repeated measurements, and the individuals are divided into an experimental group and a control group. I would like to conduct a mediation analysis on this data. Is there a model that fits this design? I had considered using Multilevel Models, but it turned out to be unsuitable.

[Erik Ruzek]

Vivian,

Welcome to Statalist!

In terms of how to proceed with your model, it would be helpful to have a little more information. First, what is the mediation pathway you want to test? Second, can you share a small amount of your data using the dataex command? It would help us understand the data structure. In the table you showed, there seems to be a formatting issue.

Generally speaking, it is helpful when your mediator is measured at an intermediate occasion between time 1 and time 2. However it seems that you measured both the outcome and mediator at time1 and time 2. In that type of design, I might instead think of treating the mediator as a moderator - a variable that influences the strength and direction of the effect of treatment on outcome changes. In terms of a simple version of such a model, it would be represented by the following regression:

regress y2 i.x##c.m1 y1
* Assuming that your mediator is a continuous variable with values ranging from 0-20
margins x, at(m1 = (0(4)20)) 
* A nice graph of the moderation effect
marginsplot