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Dear useR's, I was comparing results for a logistic regression model between different library's. themodel formula is arranged as follows: response ~ (intercept) + value + group OR: glm( response ~ (intercept) + value + group , family=binomial(link='logit')) lrm( response ~ (intercept) + value + group ) ROC( from = response ~ (intercept) + value + group ,

Hi all, I was working with the "MEMSS" & "mle4" library's under R version 2.15.1. apparently some practical functions of do not work under R 2.15.1. After searching the archives i found a mail thread on this subject, stating that these problems were partialy solved for "R 2.12.0" but only for "lmer()" not for "glmer()". Is someone aware

Dear R users, Hopefully someone can help me, Maybe I just misunderstand the function in the package? I am working with a logistic regression model. Until now I always worked with the basic glm function, where for the model was: ¡§ glm( disease ~ test.value + cnct , family=binomial(link=¡¦logit¡¦) ¡¨. This works fine when test .value and concentration (cnct) are continuous vairables. However,