[R] Problems bootstrapping multigroup SEM

[John Fox]

Dear Chad,

It's possible that I don't understand properly what you've done, but it appears as if you're passing to bootSem() the covariance matrices for the observed data rather than the case-by-variable data sets themselves. That's also what you say you're doing, and it's what the error message says. 

Moreover, if you look at the documentation in ?bootSem, you'll is that the Cov argument isn't a covariance matrix, but "a function to compute the input covariance or moment matrix; the default is cov. Use cor if the model is fit to the correlation matrix. The function hetcor in the polycor package will compute product-moment, polychoric, and polyserial correlations among mixed continuous and ordinal variables (see the first example below for an illustration)."

So what is there to bootstrap if bootSem() doesn't have access to the original data sets? I suppose that one could do a parametric bootstrap of some sort, but that's not what bootSem() does -- in implements a nonoparametric bootstrap, which requires the original data.

I hope this helps,
 John

-----------------------------------------------
John Fox, Professor
McMaster University
Hamilton, Ontario, Canada
http://socserv.socsci.mcmaster.ca/jfox/



> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Chad Danyluck
> Sent: Wednesday, August 27, 2014 12:22 PM
> To: r-help at r-project.org
> Subject: [R] Problems bootstrapping multigroup SEM
> 
> Hello,
> 
> I am having difficulty resolving an error I receive trying to bootstrap
> a
> multigroup SEM. The error (below) indicates that the model called to
> bootSem doesn't contain matrices. This is true, sort of, because I
> created
> a list of two covariance matrices for the model to call. All of this
> syntax
> works fine (a summary of "MAP.mg.sem" will produce parameter estimates,
> goodness of fit indices, etc.), however, the bootSem function does not
> run.
> Any ideas on a workaround?
> 
> MLM.MAP.Data$IAT.factor <- as.factor(IAT)
> IAT.factor <- MLM.MAP.Data$IAT.factor
> evaluative.MAP.data <- subset(data.frame(IAT.factor, exp.race,
> meditation.experience, years.meditate, repeated.iat, repeated.ERN, age,
> acceptance, awareness, FCz.GNG.150.incor, FCz.GNG.150.cor,
> FCz.stereo.150.incor, FCz.stereo.150.cor, FCz.eval.150.incor,
> FCz.eval.150.cor), IAT==2)
> stereotype.MAP.data <- subset(data.frame(IAT.factor, exp.race,
> meditation.experience, years.meditate, repeated.iat, repeated.ERN, age,
> acceptance, awareness, FCz.GNG.150.incor, FCz.GNG.150.cor,
> FCz.stereo.150.incor, FCz.stereo.150.cor, FCz.eval.150.incor,
> FCz.eval.150.cor), IAT==1)
> 
> MAP.stereotype.cov <- cov(na.omit(stereotype.MAP.data[,-1]))
> MAP.evaluative.cov <- cov(na.omit(evaluative.MAP.data[,-1]))
> MAP.cov.list <- list(stereotype=MAP.stereotype.cov,
> evaluative=MAP.evaluative.cov)
> 
> #### Specify your MSEM path model: Years Meditating, ERN, IAT####
> MAP.msem.model <- specifyModel()
> years.meditate -> repeated.ERN, path1
> years.meditate -> repeated.iat, path2
> repeated.ERN -> repeated.iat, path3
> age -> repeated.iat, path4
> years.meditate <-> years.meditate, var1
> repeated.ERN <-> repeated.ERN, var2
> age <-> age, var3
> age <-> years.meditate, cov1
> repeated.iat <-> repeated.iat, d1
> 
> MAP.mg.mod <- multigroupModel(MAP.msem.model, groups=c("stereotype",
> "evaluative"))
> 
> MAP.mg.sem <- sem(MAP.mg.mod, MAP.cov.list,
> c(nrow(stereotype.MAP.data),
> nrow(evaluative.MAP.data)), group="IAT.factor")
> 
> system.time(bootSem(MAP.mg.sem, R=100, MAP.cov.list))
> 
> Error in bootSem.msem(MAP.mg.sem.2, MAP.cov.list, R = 100) :
>   the model object doesn't contain data matrices
> 
> --
> Chad M. Danyluck
> PhD Candidate, Psychology
> University of Toronto
> Lab: http://embodiedsocialcognition.com
> 
> 
> “There is nothing either good or bad but thinking makes it so.” -
> William
> Shakespeare
> 
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> 
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