search for: glmd

I am attemting to use glmD in order to use latex(obj) afterwards. Glm works fine, glmD throws an error: > conv.go <- glmD(cbind(go.cnt,tot.cnt-go.cnt)~sn+rcs(relAge,4)+termfac+rate:termfac+ + I(relAge*term>(term-1.25))+I((prevbal/tot.cnt)*1e-4)+prod+newmort+ + I(d...

...ot; to be specified, for inline inclusion of LaTeX code in Sweave. Problems with sas.get and [.factor have been fixed. fit.mult.impute was enhanced to compute Rubin's degrees of freedom for t-statistics for scalar parameter tests, as well as to compute a missing information index. In Design, glmD works much more reliably. plotmath is now used by plot.Design. Bill Pikounis' <v_bill_pikounis at merck.com> improvements have been incorporated in bootcov to allow both cluster and group to be specified. offsets now work in lrm when NAs are present, and predict.Design now works with o...

...ot; to be specified, for inline inclusion of LaTeX code in Sweave. Problems with sas.get and [.factor have been fixed. fit.mult.impute was enhanced to compute Rubin's degrees of freedom for t-statistics for scalar parameter tests, as well as to compute a missing information index. In Design, glmD works much more reliably. plotmath is now used by plot.Design. Bill Pikounis' <v_bill_pikounis at merck.com> improvements have been incorporated in bootcov to allow both cluster and group to be specified. offsets now work in lrm when NAs are present, and predict.Design now works with o...

Hi, I am doing a retrospective analysis on a cohort from a designed trial, and I am fitting the model fit<-glmD(survived ~ Covariate*Therapy + confounder,myDat,X=TRUE, Y=TRUE, family=binomial()) My covariate has three levels ("A","B" and "C") and therapy has two (treated and control), confounder is a continuous variable. Also patients were randomized to treatment in the trial,...

Hi all, I have fitted a gee model with the gee package and included restricted cubic spline functions. Here is the model: chol.g <- gee(SKIN ~ rcs(CHOLT, 3), id=ID, data=chol, family=binomial(link="logit"), corstr="exchangeable") To extract the log odds I use: predict.glm(chol.g, type = "link") Now I want to compute the logg odds for specific CHOLT values

Dear all, Is the restricted cubic spline function working properly in the glm model? We used glm(y~rcs(x,5), family=binomial) but it seems that for some theoretical reasons the rcs, restricted cubic spline function can not be fitted by a glm function. Is this correct? Regards, Jan ((Originally, we used lrm(y~ rcs(x,5)) but we couldn't find how to derive the AIC value of the fitted model.

This is my first post to this list so I suppose a quick intro is in order. I've been using SPLUS 2000 and R1.6.2 for just a couple of days, and love S already. I'm reading MASS and also John Fox's book - both have been very useful. My background in stat software was mainly SPSS (which I've never much liked - thanks heavens I've found S!), and Perl is my tool of choice for