I'm having some difficulty with graphing outputs of a GLM model I've been working. I have count data for both my predictor (only 1) and response variables, and I have pseudoreplication which I've modeled as a random effect. The odTest() from pscl:: indicated that the negative binomial distribution fit better than Poisson, and I then proceeded by estimating theta from glm.nb. My residual plot of m1 looks great, and now I'd like an output showing the relationship between BERRIES and the respose, but I can't seem to get "BERRIES" on the x-axis. It keeps spitting out "INDEX" which is just all my numbered observations from 1 to 121, and therefore not to scale. I did try creating a new vector to plot the data, but I got an error message (see below). Does anyone have suggestions on where to look to solve this problem?
Erin Latham, M.GIS Candidate, Geography University of Calgary, AB, Canada > m0 <- glm.nb(MANUAL ~ BERRIES + BUSHID , data=a) >theta<-m0$theta > m1 <- glmmPQL(MANUAL ~ BERRIES, random = ~ 1|BUSHID, data=a, > family=negative.binomial(theta)) > summary(m1) Linear mixed-effects model fit by maximum likelihood Data: a AIC BIC logLik NA NA NA Random effects: Formula: ~1 | BUSHID (Intercept) Residual StdDev: 1.081722 0.6577578 Variance function: Structure: fixed weights Formula: ~invwt Fixed effects: MANUAL ~ BERRIES Value Std.Error DF t-value p-value (Intercept) 7.602133 0.23105575 91 32.90172 0 BERRIES 0.001369 0.00023395 28 5.85324 0 Correlation: (Intr) BERRIES -0.485 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -2.14692244 -0.52715093 -0.02833408 0.48002141 2.70931877 Number of Observations: 121 Number of Groups: 30 > MyData<-data.frame(BERRIES = seq(from =20, to=3600, by=100)) > e<-predict(m1,MyData,type="response") Error in predict.lme(object, newdata, level = level, na.action = na.action) : Cannot evaluate groups for desired levels on "newdata" ______________________________________________ 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.