Message/Author |
|
|
Hi, I am working on a proposal and would like to know if it's possible to do a path analysis to examine a fully longitudinal indirect effect with the data I will have. The data include stratification (3 countries), survey weights, and clustering - and I expect I will need to use multiple imputation with them. There are about 500 individuals in the sample, all of whom have data for the outcome variable. At time 1, I have a dichotomous predictor variable and I can control for the mediator at this time as well. At time 2, I have a sum score mediator and I can control for the dichotomous outcome. At time 3, I have a dichotomous outcome variable. In reading through the message boards and several papers, it seems to me that Mplus can account for much, if not all, of these things individually using: TYPE=COMPLEX WEIGHTS=WeightVar CLUSTER=StratVar Estimator= WLSMV But what I don't know is if Mplus can do all of these things together - and/ or if I am missing anything else that I should be aware of. I am also not sure whether, with a sample of 500, it makes sense to use the Sobel test or bootstrapping - and which might work best in Mplus with this data and analysis. I would very much appreciate some advice. Thank you! |
|
|
I maybe should have included that I think I am going to need to do a log-binomial model rather than a logistic model. This is because my outcome is greater than 10% (VanderWeele, 2016 Mediation Analysis, A Practitioner's Guide) |
|
|
WLSMV and ML can do these things together. Even though your binary outcome has prevalence > 10%, you can use the Mplus counterfactually-defined indirect/direct effects for logistic link - they don't assume a rare event for the outcome as the VanderWeele approximate odds ratio approach does. See chapter 8 of our RMA book. |
|
|
Thank you so much. This is very encouraging to hear, and I will check out your book as well. |
|
|
Hi again, I wanted to ask about this whether it is possible to obtain a 95% confidence interval with imputed data. It is possible I may need to impute this data. Thank you! |
|
|
Yes. You can use the formula Estimate +-1.96*SE or you can have Mplus do that for you with the option output:cint; |
|
|
Thank you. Would that be a bias-corrected bootstrap 95% CI? Is that possible to use with imputed data? |
|
|
No and it is not possible at this point in Mplus. It would be the above symmetric CI. |
|
Back to top |