svyglm {survey} | R Documentation |
Fit a generalised linear model to data from a complex survey design, with inverse-probability weighting and with standard errors corrected for cluster sampling.
svyglm(formula, design, subset=NULL, ...) svrepglm(formula, design, subset=NULL, ..., rho=NULL, return.replicates=FALSE, na.action) ## S3 method for class 'svyglm': summary(object, correlation = FALSE, ...)
formula |
Model formula |
design |
Survey design from svydesign or svrepdesign . Must contain all variables
in the formula |
subset |
Expression to select a subpopulation |
... |
Other arguments passed to glm or
summary.glm |
rho |
For replicate BRR designs, to specify the paramter for Fay's variance method |
return.replicates |
Return the replicates as a component of the result? |
object |
A svyglm object |
correlation |
Include the correlation matrix of parameters? |
na.action |
Handling of NAs |
In svyglm
, standard errors for cluster-sampled designs are computed using a
linearisation estimate (in the absence of strata this is equivalent to
the Huber/White sandwich formula in GEEs). Most of these computations
are done in svyCprod
. In svrepglm
, replicate
weight methods are used.
There is no anova
method for svyglm
as the models are not
fitted by maximum likelihood. The function regTermTest
may
be useful for testing sets of regression terms.
An object of class svyglm
.
Thomas Lumley
svydesign
,
svrepdesign
,as.svrepdesign
, glm
,
svyCprod
, svy.varcoef
,regTermTest
data(api) glm(api00~ell+meals+mobility, data=apipop) dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc) dclus2<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2) rstrat<-as.svrepdesign(dstrat) rclus2<-as.svrepdesign(dclus2) summary(svyglm(api00~ell+meals+mobility, design=dstrat)) summary(svyglm(api00~ell+meals+mobility, design=dclus2)) summary(svrepglm(api00~ell+meals+mobility, design=rstrat)) summary(svrepglm(api00~ell+meals+mobility, design=rclus2)) ## use quasibinomial, quasipoisson to avoid warning messages summary(svyglm(sch.wide~ell+meals+mobility, design=dstrat, family=quasibinomial()))