On 8/19/05, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote: > I fit the following model using glmmPQL from MASS: > > fit.glmmPQL <- > glmmPQL(ifelse(class=="Disease",1,0)~age+x1+x2,random=~1|subject,family=binomial) > summary(fit.glmmPQL) > > The response is paired (pairing denoted by subject), although some > subjects only have one response. Also, there is a perfect positive > correlation between the paired responses. x1 and x2 can and do differ > within each pair. Here is the output: > > > summary(fit.glmmPQL) > Linear mixed-effects model fit by maximum likelihood > Data: fernando > AIC BIC logLik > 30.51277 49.25655 -9.256384 > > Random effects: > Formula: ~1 | subject > (Intercept) Residual > StdDev: 8.284993 4.113725e-09
Notice the value of the residual standard deviation. It's far too small (it should be approximately 1 for a binomial-response model fit by IRLS). You have perfect prediction in your model and surprisingly that is a problem in these models. > > Variance function: > Structure: fixed weights > Formula: ~invwt > Fixed effects: ifelse(class == "Disease", 1, 0) ~ age + x1 + x2 > Value Std.Error DF t-value p-value > (Intercept) -35.01862 2.4414559 123 -14.3 0 > age 0.59026 0.0441817 123 13.4 0 > x1 1.39317 0.0000014 41 1000507.2 0 > x2 0.93695 0.0000010 41 915150.3 0 > Correlation: > (Intr) age x2 > age -0.952 > x1 0.000 0.000 > x2 0.000 0.000 -0.057 > > Standardized Within-Group Residuals: > Min Q1 Med Q3 Max > -2.939213e+00 -2.509951e-07 -1.169248e-07 2.999710e-06 3.825035e+00 > > Number of Observations: 168 > Number of Groups: 125 > > > The t-values are huge and the se's are correspondingly tiny. The model > does a great job of discriminating between disease and no disease. But I > have a feeling there is something wrong here. Is there something wrong > with the type of model I'm trying to fit? If it weren't for the pairing I > would just have used glm. Any insights would be appreciated. > > Rick B. > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
