survey (version 3.3-2)

svyglm: Survey-weighted generalised linear models.

Description

Fit a generalised linear model to data from a complex survey design, with inverse-probability weighting and design-based standard errors.

Usage

## S3 method for class 'survey.design':
svyglm(formula, design, subset=NULL, ...)
## S3 method for class 'svyrep.design':
svyglm(formula, design, subset=NULL, ..., rho=NULL,
return.replicates=FALSE, na.action)
## S3 method for class 'svyglm':
summary(object, correlation = FALSE,  ...)

Arguments

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 parameter for Fay's variance method, giving weights of rho and 2-rho

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

Value

• An object of class svyglm.

Details

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.

See Also

svydesign, svrepdesign,as.svrepdesign, glm, regTermTest

Examples

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(svyglm(api00~ell+meals+mobility, design=rstrat))
  summary(svyglm(api00~ell+meals+mobility, design=rclus2))

  ## use quasibinomial, quasipoisson to avoid warning messages
  summary(svyglm(sch.wide~ell+meals+mobility, design=dstrat, family=quasibinomial()))