Hello -
I am analysing some survey data using the svyglm() command in the survey
package. Since I am doing binomial regression, the family I'm choosing is
'quasibinomial', since this suppresses the warning that comes about from the
inclusion of non-integer outcomes due to weights.
I am looking at doing some proper diagnostics of my model. However, the only
goodness-of-fit method I can see from the mailing list is regtermtest(), which
essentially tests the significance of additional terms, or the hypothesis that
the model is better than the intercept.
My questions are:
- is it possible to obtain residual 'working' deviance after the Rao-Scott
method, which would indicate deviance with respect to the saturated model?
- by way of corrollary (or substitute), can deviance residuals be obtained?
- given that svyglm appears to give the raw residuals through the
residuals([svyglm object]) command, does anyone know of a good reference on how
to effectively use pearson residuals for model diagnostics (on the basis that
deviance ones are unavailable).
Many thanks.
Marko Stojovic
MSc Applied Statistics student, Birkbeck College, London
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