I think I can now answer my own questions: Henric Nilsson ([EMAIL PROTECTED]) wrote*:
>1. I can't seem to get the correct p-values from anova.glm() for the F-tests when >supplying the dispersion argument and having fitted the model using >family=quasibinomial. Using family=quasibinomial does exactly what it says: It fits a quasi-likelihood model with mean=mu and variance=mu(1-mu). Hence, supplying the dispersion argument results in R treating this as a known value, i.e. not estimated from data, in which case the F-test shouldn't be used and therefore returns the same p-value as the Chi- squared test. >2. When using summary.glm() on a glm object fitted using family=quasibinomial the >reported tests are t-tests. Why? This makes sense since we're estimating the dispersion parameter. Can't really remember what confused me here... //Henric ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
