Hello,
I would like to run a mediation analysis with a logit model using a binary independent/treatment variable (X), a binary mediator (M), and a binary dependent variable (Y). I also need to do sensitivity analysis along with the mediation analysis because there are some potential unobserved variables confounding the relationship between X and Y.
With that in mind, I have identified -paramed- (Emsley et al. forthcoming; Valeri and Vanderweele 2013) and -medeff- (Imai, Keele, and Tingley 2010), both of which are user-written programs, as providing the most potential utility in terms of what I need, but there are some remaining questions and issues:
1.) I can't seem to find any Stata commands that execute such sensitivity analysis for the -paramed- package. Has someone written a set of sensitivity analysis commands to use with -paramed- that I have missed, or is there another set of substitutable sensitivity analysis commands that will work in conjunction with -paramed-?
2.) As an alternative to -paramed-. -medeff- allows dichotomous outcomes and mediators, and it contains a sensitivity analysis command, -medsens-. However, it appears that -medsens- is only applicable in cases where there are unobserved variables that confound the relationship between the mediator (M) and the outcome (Y). In my analysis, the unobserved confounding variables confound the relationship between the treatment (X) and the outcome, not the relationship between the mediator and the outcome. Am I correct in my conclusion that -medsens- does not allow for confounders of the treatment-outcome relationship? If not, can anyone point me to a source or set of commands within -medsens-/-medeff- that will allow for this type of confounding? If I am correct, are there a set of substitutable commands that allow for confounding of the treatment-outcome relationship and that will work in conjunction with -medsens-/-medeff-?
Thanks in advance for any insight,
--David
References:
Emsley, R.A., H. Liu, G. Dunn, L. Valeri, and T.J. VanderWeele. forthcoming (2014)."Paramed: A Command to Perform Causal Mediation Analysis Using Parametric Models." The Stata Journal.
Imai, K., L. Keele, and D. Tingley. 2010. "A General Approach to Causal Mediation Analysis." Psychological Methods, 15(4): 309-34.
Valeri, L., and T.J. VanderWeele. 2013. "Mediation Analysis Allowing for Exposure–Mediator Interactions and Causal Interpretation: Theoretical Assumptions and Implementation With SAS and SPSS Macros." Psychological Methods, 18(2): 137-50.
I would like to run a mediation analysis with a logit model using a binary independent/treatment variable (X), a binary mediator (M), and a binary dependent variable (Y). I also need to do sensitivity analysis along with the mediation analysis because there are some potential unobserved variables confounding the relationship between X and Y.
With that in mind, I have identified -paramed- (Emsley et al. forthcoming; Valeri and Vanderweele 2013) and -medeff- (Imai, Keele, and Tingley 2010), both of which are user-written programs, as providing the most potential utility in terms of what I need, but there are some remaining questions and issues:
1.) I can't seem to find any Stata commands that execute such sensitivity analysis for the -paramed- package. Has someone written a set of sensitivity analysis commands to use with -paramed- that I have missed, or is there another set of substitutable sensitivity analysis commands that will work in conjunction with -paramed-?
2.) As an alternative to -paramed-. -medeff- allows dichotomous outcomes and mediators, and it contains a sensitivity analysis command, -medsens-. However, it appears that -medsens- is only applicable in cases where there are unobserved variables that confound the relationship between the mediator (M) and the outcome (Y). In my analysis, the unobserved confounding variables confound the relationship between the treatment (X) and the outcome, not the relationship between the mediator and the outcome. Am I correct in my conclusion that -medsens- does not allow for confounders of the treatment-outcome relationship? If not, can anyone point me to a source or set of commands within -medsens-/-medeff- that will allow for this type of confounding? If I am correct, are there a set of substitutable commands that allow for confounding of the treatment-outcome relationship and that will work in conjunction with -medsens-/-medeff-?
Thanks in advance for any insight,
--David
References:
Emsley, R.A., H. Liu, G. Dunn, L. Valeri, and T.J. VanderWeele. forthcoming (2014)."Paramed: A Command to Perform Causal Mediation Analysis Using Parametric Models." The Stata Journal.
Imai, K., L. Keele, and D. Tingley. 2010. "A General Approach to Causal Mediation Analysis." Psychological Methods, 15(4): 309-34.
Valeri, L., and T.J. VanderWeele. 2013. "Mediation Analysis Allowing for Exposure–Mediator Interactions and Causal Interpretation: Theoretical Assumptions and Implementation With SAS and SPSS Macros." Psychological Methods, 18(2): 137-50.
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