svyglm                package:survey                R Documentation

_S_u_r_v_e_y-_w_e_i_g_h_t_e_d _g_e_n_e_r_a_l_i_s_e_d _l_i_n_e_a_r _m_o_d_e_l_s.

_D_e_s_c_r_i_p_t_i_o_n:

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

_U_s_a_g_e:

     ## 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,  ...) 

_A_r_g_u_m_e_n_t_s:

 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

_D_e_t_a_i_l_s:

     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.

_V_a_l_u_e:

     An object of class 'svyglm'.

_A_u_t_h_o_r(_s):

     Thomas Lumley

_S_e_e _A_l_s_o:

     'svydesign', 'svrepdesign','as.svrepdesign', 'glm', 'regTermTest'

_E_x_a_m_p_l_e_s:

       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()))

      

