On Sat, 31 Jul 2010, aline uwimana wrote:
This message is for those familiar with the survey package. I need to do
regression logistic and choose the best model which explain the impact of the
indepndent variables by using AIC,BIC,...
> sum.coef<-summary(svyglm(y~x1+x2+x3, design=design, family=quasibinomial(),
data=data))$deviance
is this the correct way for obtaining the deviance.
You can use the deviance() function to get a number. This number isn't really
the deviance, because svyglm() doesn't use maximum likelihood estimation. It
doesn't have a chi-squared distribution, for example. It is the deviance that
would be computed if the weights were precision weights and were rescaled to
sum to the sample size. There isn't a real deviance.
The reason this number is reported is that, although differences in deviance do not have
a chi-squared distribution, they do asymptotically have a known distribution and this
gives the Rao-Scott 'working deviance' tests. These tests are widely used for loglinear
models but also apply to generalized linear models and the Cox model. The function
regTermTest() does Rao-Scott tests with the method="LRT" option.
-thomas
Thomas Lumley
Professor of Biostatistics
University of Washington, Seattle
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