RE: st: Testing for mediation with categorical mediators and complex survey data?

[Cameron McIntosh <cnm100@hotmail.com>]

Adena,
The endogeneity issue should be attended to, as John says. You may also find the following helpful:
Kuha, J., & Goldthorpe, J.H. (2010). Path analysis for discrete variables: the role of education in social mobility. Journal of the Royal Statistical Society: Series A (Statistics in Society), 173(2), 351–369.

Eshima, N., Tabata, M., & Zhi, G. (2001). Path analysis with logistic regression models: effect analysis of fully recursive causal systems of categorical variables. Journal of the Japanese Statistical Society, 31(1), 1-14. http://www.scipress.org/journals/jjss/pdf/3101/31010001.pdf

Roodman, D. (2011). Fitting fully observed recursive mixed-process models with cmp. The Stata Journal, 11(2), 159-206.http://www.stata-journal.com/article.html?article=st0224http://ideas.repec.org/c/boc/bocode/s456882.html

Samani, E.B., & Ganjali, M. (2010). Analysis of Mixed Correlated Ordinal and Continuous Responses with and Without Missing Data in R: Latent Variable Approach. Australian Journal of Basic and Applied Sciences, 4(8), 3815-3834. http://www.insipub.com/ajbas/2010/3815-3834.pdf

de Leon, A.R., Soo, A., & Williamson, T. (2011). Classification with discrete and continuous variables via general mixed-data models. Journal of Applied Statistics, 38(5), 1021–1032.http://math.ucalgary.ca/~adeleon/JAS_class.pdf

de Leon, A.R., & Carrière, K.C. (2007). General mixed-data model: extension of general location and grouped continuous models. Canadian Journal of Statistics, 35(4), 533–548.http://math.ucalgary.ca/~adeleon/CJS_gmdm.pdf

Song, X.-Y., Lee, S.-Y., Cai, J.-H., So, W.-Y., Ma, C.-W., & Chan, C.-N.J. (2009). Non-linear structural equation models with correlated continuous and discrete data. British Journal of Mathematical and Statistical Psychology, 62(2), 327–347.

Rao, P.V., Li, H., & Roth, J. (2008). Recursive Path Models when Both Predictor and Response Variables are Categorical. Journal of Statistical Theory and Practice, 2(4), 663-676.http://mch.peds.ufl.edu/recent_pubs/Rao.pdf

Note that many of these are not Stata solutions... any of them should allow resampling to be grafted on to the analysis manually (not really rocket science to program, once you know which resampling method you want to use), and you might want to consider linearization as an alternative:
Demnati, A., & Rao, J.N.K. (2010). Linearization variance estimators for model parameters from complex survey data. Survey Methodology, 36(2), 193-201. http://www.statcan.gc.ca/pub/12-001-x/2010002/article/11381-eng.pdf
Demnati, A., & Rao, J.N.K. (2004). Linearization variance estimators for survey data. Survey Methodology, 30(1), 17-26.
Cam
> Date: Fri, 16 Dec 2011 14:09:51 +0100
> From: John.Antonakis@unil.ch
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Testing for mediation with categorical mediators and complex survey data?
> 
> Hi:
> 
> The thing to worry about, before figuring out the the indirect effect is 
> whether the mediator is endogenous. It is critical to understand this 
> issue first before testing for mediation or sgmediation; these methods 
> use OLS and won't do the trick. You need an instrumental variable 
> estimator as discussed here in the archives:
> 
> http://www.stata.com/statalist/archive/2011-10/msg00801.html
> (if this is quite new to you, make sure you see the podcast, which is 
> linked in the message)
> 
> So bootstrap the SE of the indirect effect when the estimate is 
> (possibly) inconsistent will not help.
> 
> As for the estimation command, check out the user-written command -cmp-; 
> I think that it should be able to handle what you want.  Ensure to use 
> vce(robust) (then you don't have to worry about the SEs).
> 
> After you estimate the model, you can test for the significance of an 
> indirect effect using nlcom, e.g., (where Eq. 1 is the first stage 
> equation of x predicting the mediator m, and Eq. 2 is the second stage 
> equation on the mediator m predicting y).
> 
> [eq1]x*[eq2]m
> (you can see how to do a "manual" Sobel test in the link above too)
> 
> This is the Sobel test.
> 
> HTH,
> J.
> 
> __________________________________________
> 
> Prof. John Antonakis
> Faculty of Business and Economics
> Department of Organizational Behavior
> University of Lausanne
> Internef #618
> CH-1015 Lausanne-Dorigny
> Switzerland
> Tel ++41 (0)21 692-3438
> Fax ++41 (0)21 692-3305
> http://www.hec.unil.ch/people/jantonakis
> Associate Editor
> The Leadership Quarterly
> __________________________________________
> 
> 
> On 16.12.2011 13:53, Galinsky, Adena M. wrote:
> > Hello all,
> >
> > I would like to test for mediation by calculating Sobel-Goodman tests for mediated effects, using the Preacher and Hayes method of bootstrapping the standard error of the mediated effects.
> >
> > I understand that the standard way to do this in Stata is to use sgmediation.
> >
> > However, sgmediation does not work if either the Independent Variable (IV) or Mediating Variable (MV) is categorical, nor does it work with the svy command.
> >
> > For my analysis, I am using categorical IV's and MV's (the Dependent Variable (DV) is continuous) that were collected in a survey with complex design (i.e., that are appropriately analyzed using the svy commands)
> >
> > (I've already looked at "How can I do mediation analysis with a categorical IV in Stata?" found here: http://www.ats.ucla.edu/stat/stata/faq/mediation_cativ.htm. This page recommended using sureg - a command that does not work with svy nor with categorical mediating variables. It thus did not answer my question since a. It only covers the case when the IV is categorical, not when the MV is categorical and b. It does not mention what to do when using complex survey data and c. It does not mention Sobel-Goodman tests (though presumably I could write a program to calculate these tests, if I could find a solution to a. and b.)
> >
> > Can you recommend what I should do?
> >
> > Thank you for your help!
> >
> > best,
> > Adena
> >
> > ps  By the way, it looks like Hayes has a new SPSS macro that can handle categorical IV's and MV's - has anyone converted this into a stata version? (The SPSS version is here: http://www.afhayes.com/spss-sas-and-mplus-macros-and-code.html)
> >
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