I am new to the mediation analysis and i am trying to find my way...
So, I have the following dataset:
X's : 5 independent variables (D, E, F, G, H), where H is the sum of the other 4 (probably not very wise to be in the analysis, and also the models produces an error whrn i include it, and so i left it out ), continuous
M's : 1 mediator (B), continuous
Y : 1 response (I), continuous
Z : 1 covariate (not in the output yet), continuous
I also have some missing values for some of them (around 6-7%).
So, i have first to use MICE to input and then run the mediation analysis. But, as i found out it is not straightforward to combine them, so i used this example here. They use the lavaan package in R.
The output i got, is the following :
Can somebody please help me interpret this output here ? I am very confused with the several predictors in the model and i don't know how to assess mediation or not...And even if it is appropriate to add all these variables in a model like this..
And finally, if you know something more elegant about the combination of MICE and mediation analysis...
Thanks
mediation
package ormedflex
package in R.Mediation
package is more mature and has more features but has some limits for model type. (Feel free to make this a comment once you see this). $\endgroup$dataarg
, seems like it does not have rows, maybe it requires your dataset to be in a different format. $\endgroup$