# Resampling variances for svy2lme Computes variance estimates for the weighted-pairwise-likelihood linear mixed models fitted by `svy2lme` using replicate weights. The replicate weights for a pair are obtained by dividing by the sampling weight and then multiplying by the replicate weight. There will be a warning if the ratio of replicate weight to sampling weight differs for observations in the same pair. ```r boot2lme(model, rdesign, verbose = FALSE) ## S3 method for class 'boot2lme' vcov(object, parameter=c("beta", "theta","s2", "relSD" ,"SD","relVar","fullVar"), ...) ``` ## Arguments - `model`: A model returned by `svy2lme` with the `devfun=TRUE` option - `rdesign`: replicate-weights design corresponding to the design used to fit the model, see example - `verbose`: print progess information? - `object`: returned by `boot2lme` - ``...``: for method compatibility - `parameter`: Variance matrix for: regression parameters, relative variance parameters on Cholesky square root scale, residual variance, relative standard errors of random effects, standard errors of random effects, entire relative variance matrix, entire variance matrix ## Details The variance is estimated from the replicates `thetastar` and original point estimate `theta` as `scale*sum(rscales* (thetastar-theta)^2)`. ## Returns For `boot2lme`, an object of class `boot2lme` with components - **theta**: replicates of variance parameters (on Cholesky square root scale) - **beta**: replicates of regression parameters - **D**: replicates of relative variance matrix - **scale,rscales**: from the input - **formula**: model formula from the input For the `vcov` method, a variance matrix. ## Examples ```r data(api, package="survey") # two-stage cluster sample dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2) m0<-svy2lme(api00~(1|dnum)+ell+mobility, design=dclus2,return.devfun=TRUE) jkdes<-as.svrepdesign(dclus2, type="mrb") jkvar<-boot2lme(m0,jkdes) SE(jkvar, "beta") SE(jkvar, "SD") SE(jkvar,"s2") m1<-svy2lme(api00~(1|dnum)+ell+mobility, design=dclus2,return.devfun=TRUE, all.pairs=TRUE, subtract.margins=TRUE) jk1var<-boot2lme(m1,jkdes) SE(jk1var, "beta") SE(jk1var, "SD") ##takes a few minutes data(pisa) pisa$w_condstuwt<-with(pisa, w_fstuwt/wnrschbw) pisa$id_student<-1:nrow(pisa) dpisa<-survey::svydesign(id=~id_school+id_student, weight=~wnrschbw+w_condstuwt, data=pisa) m<-svy2lme(isei~(1+female|id_school)+female+high_school+college+one_for+both_for+test_lang, design=dpisa, return.devfun=TRUE,method="nested") bpisa<-as.svrepdesign(dpisa, type="bootstrap", replicates=100) b<-boot2lme(m, bpisa, verbose=TRUE) str(b) vcov(b,"beta") vcov(b,"s2") ## SE() inherits the parameter= argument SE(b,"beta") SE(b,"theta") SE(b,"SD") ```

boot2lme function