In the following simple example, the coefficients returned by glm() and rxGlm() will match but those returned by rxLogit() may be different.
myFormula <- as.formula("y ~ x1 + x2 + x3 ")
model <- rxLogit( myFormula, data = sampleData)
modelGLM <- glm(myFormula,family=binomial(logit),data=sampleData)
modelrxGLM <- rxGlm(myFormula,family=binomial(logit), data=sampleData)
For rxLogit, initialValues defaults to NULL. From the help for rxLogit: "The initial values will be estimated based on a linear regression. This can speed up convergence significantly in many cases. If the model fails to converge using these values, estimation is automatically re-started using the NA option for the initial values." If NA is used, "Initial values of the parameters are computed by a weighted least squares step". For rxGlm, initialValues defaults to NA.
So if the results from rxLogit are unexpectedly different, it may be that the model does converge with initialValues=NULL and the function returns different results. When running the example with initalValues=NA in the rxLogit(), all results match.
Article ID: 3104219 - Last Review: 29 Oct 2015 - Revision: 1