Dear sstewart, The model appears to reflect the path diagram, assuming that you intend to allow the exogenous variables to be correlated and want the errors to be uncorrelated.
This is one way to model the binary variable reuse. An alternative would be to fit the equation for intent by least-squares regression (assuming that the relationships are linear, etc.), and the equation of reuse by, e.g., logistic regression (again assuming that the model is correctly specified). If you're right that the effects of the exogenous variables are entirely mediated by intent, then if you put these variables in the equation for reuse, their coefficients should be small. I hope this helps, John -------------------------------- John Fox Senator William McMaster Professor of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada web: socserv.mcmaster.ca/jfox > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of R Help > Sent: May-24-10 11:18 AM > To: r-help > Subject: [R] Path Analysis > > Hello list, > > I'm trying to make sure that I'm performing a path analysis correctly > using the sem package. the figure at > http://flame.cs.dal.ca/~sstewart/regressDiag.png has a detailing of > the model. > > The challenge I'm having is that reuse is an indicator (0/1) variable. > > Here's the code I'm using: > > corr = > hetcor(dat[,c('intent','exposure','benefit','norms','childBarrier','parentBa r > rier','knowBenefit','recuse')],use="pairwise.complete.obs")$correlations > modMat = matrix(c( > 'exposure -> intent', 'gam11',NA, > 'benefit -> intent', 'gam12',NA, > 'norms -> intent', 'gam13',NA, > 'childBarrier -> intent', 'gam14',NA, > 'parentBarrier -> intent', 'gam15',NA, > 'knowBenefit -> intent', 'gam16',NA, > 'intent<->intent','psi11',NA, > 'intent->recuse','gam21',NA, > 'recuse<->recuse','psi22',NA), > ncol=3,byrow=T) > model4 = > sem(modMat,corr,N=1520,fixed.x=c('exposure','benefit','norms','childBarrier' , > 'parentBarrier','knowBenefit')) > > Is this correctly modeling my diagram? I'm not sure if a) I'm dealing > with the categorical variable correctly, or b) whether fixed.x is > accurately modeling the correlations for me. > > Any help would be appreciated. I'm also looking into creating a plot > function within R (similar to the path.diagram function, but using R > plots). If I get something useful I'll try and post it back > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
