How to report good suitability for an svyglm object?

Question

question about the survey package in R. I know that it is very simple, but I did not find anything. So:

library(survey) data(api) dclus2 <- svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) summary(svyglm(api00 ~ ell + meals + mobility, design = dclus2)) Call: svyglm(formula = api00 ~ ell + meals + mobility, design = dclus2) Survey design: svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 819.2791 21.3900 38.302 4.65e-13 *** ell -0.5167 0.3240 -1.595 0.139 meals -3.1232 0.2781 -11.231 2.29e-07 *** mobility -0.1689 0.4449 -0.380 0.711 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for gaussian family taken to be 3157.85) Number of Fisher Scoring iterations: 2 

Is there something like an R-square or any other statistics that would give the reader an impression of how good the model is for the data?

thanks.

Answer 1

There is a package that appeared at the end of 2016 that I found called "poliscidata", which has a fit.svyglm function that returns R square and Adj. R Square outputs for svyglm objects. I have used it with success.