bootweights              package:survey              R Documentation

_C_o_m_p_u_t_e _s_u_r_v_e_y _b_o_o_t_s_t_r_a_p _w_e_i_g_h_t_s

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

     Bootstrap weights for infinite populations are created by sampling
     with replacement from the PSUs in each stratum. 'subbootweights()'
     samples 'n-1' PSUs from the 'n' available (Rao and Wu),
     'bootweights' samples 'n' (Canty and Davison).

     'bootweights()' is most useful when the strata are large and may
     have large sampling fractions, 'subbootweights()' is useful when
     the strata have a small number of PSUs and the sampling fractions
     are small.

     This bootstrap is strictly appropriate only when the first stage
     of sampling is a simple or stratified random sample of PSUs with
     or without replacement, and not (eg) for PPS sampling.

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

     bootweights(strata, psu, replicates = 50, fpc = NULL,
              fpctype = c("population", "fraction", "correction"),
              compress = TRUE)
     subbootweights(strata, psu, replicates = 50,
              compress = TRUE)

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

  strata: Identifier for sampling strata (top level)

     psu: Identifier for primary sampling units

replicates: Number of bootstrap replicates

     fpc: Finite population correction 

 fpctype: Is 'fpc' the population size, sampling fraction, or
          1-sampling fraction?

compress: Should the replicate weights be compressed?

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

     A set of replicate weights

_R_e_f_e_r_e_n_c_e_s:

     Canty AJ, Davison AC. (1999) Resampling-based variance estimation
     for labour force surveys. The Statistician 48:379-391

     Rao JNK, Wu CFJ. Bootstrap inference for sample surveys. Proc
     Section on Survey Research Methodology. 1993 (866-871)

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

     'as.svrepdesign'

