svyCprod               package:survey               R Documentation

_C_o_m_p_u_t_a_t_i_o_n_s _f_o_r _s_u_r_v_e_y _v_a_r_i_a_n_c_e_s

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

     Computes the sum of products needed for the variance of survey
     sample estimators.

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

     svyCprod(x, strata, psu, fpc, nPSU,
           lonely.psu=getOption("survey.lonely.psu"))

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

       x: A vector or matrix

  strata: A vector of stratum indicators, or 'NULL'

     psu: A vector of cluster indicators or 'NULL'

     fpc: A data frame of population stratum sizes or 'NULL'

    nPSU: Table of original sample stratum sizes (or 'NULL')

lonely.psu: One of '"remove"', '"adjust"', '"fail"', '"certainty"'. See
          Details below

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

     The observations for each cluster are added, then centred within
     each stratum and the outer product is taken of the row vector
     resulting for each cluster.  This is added within strata,
     multiplied by a degrees-of-freedom correction and by a finite
     population correction (if supplied) and added across strata.  

     If there are fewer clusters (PSUs) in a stratum than in the
     original design extra rows of zeroes are added to 'x' to allow the
     correct subpopulation variance to be computed.

     The variance formula gives 0/0 if a stratum contains only one
     sampling unit. The options to handle this are '"fail"' to give an
     error, '"remove"' or '"certainty"' to give a variance contribution
     of 0 for the stratum, and '"adjust"' to center the stratum at the
     grand mean rather than the stratum mean.  The choice is controlled
     by setting 'options(survey.lonely.psu)'. If this is not done the
     factory default is '"fail"'. Using '"adjust"' is conservative, and
     it would often be better to combine strata in some intelligent
     way.

     The '"remove"'and '"certainty"' options give the same result, but
     '"certainty"' is intended for situations where there is only one
     PSU in the population stratum, which is sampled with certainty
     (also called `self-representing' PSUs or strata). With
     '"certainty"' no warning is generated for strata with only one
     PSU.  The factory default is '"fail"'.

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

     A covariance matrix

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

     Thomas Lumley

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

     'svydesign', 'svy.varcoef'

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

