haps
2012-Oct-12 21:02 UTC
[R] goodness of fit for logistic regression with survey package
I am making exploratory analyses on a complex survey data by using survey package. Could you help me how to see the goodness of fit for the model below? Should I use AIC, BIC, ROC, or what? What code would let me run a goodness of fit test for the model? Here are my codes: #incorporating design effects#> mydesign <- svydesign(id=~clust, strata=~strat, weights=~sweight, > data=mydata)#logistic regression model#> model1 <- svyglm(y ~ x1 + x2+ x3 + x4 + x5, design = mydesign, > data=(mydata),family=quasibinomial())#I tried loglik function, but didn't work#> logLik(model1)[1] 8753.057 Warning message: In logLik.svyglm(model1) : svyglm not fitted by maximum likelihood. #I did the following which didn't work either#> with(model1, null.deviance - deviance)[1] 1039.695> with(model2, df.null - df.residual)[1] 6565> with(model2, pchisq(null.deviance - deviance, df.null - df.residual,+ lower.tail = FALSE)) [1] 1 -- View this message in context: http://r.789695.n4.nabble.com/goodness-of-fit-for-logistic-regression-with-survey-package-tp4646044.html Sent from the R help mailing list archive at Nabble.com.