mipo                  package:mice                  R Documentation

_M_u_l_t_i_p_l_y _I_m_p_u_t_e_d _P_o_o_l_e_d _A_n_a_l_y_s_i_s

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

     The "mipo" object is generated by the 'lm.mids' and 'glm.mids'
     functions. The "mipo" class of objects has methods for the
     following generic functions: print, summary.

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

     print.mipo(x,...)
     summary.mipo(object,...)

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

x, object: An object containing the m fit objects of a complete data
          analysis,  plus some additional information.

     ...: not used.

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

    call: The call that created the mipo object.

   call1: The call that created the mira object that was used in
          'call'.

   call2: The call that created the mids object that was used in
          'call1'.

    nmis: An array containing the number of missing observations per
          column.

       m: Number of multiple imputations.

    qhat: An m x 'npar' matrix containing the complete data estimates
          for the 'npar' paremeters of the m complete data analyses.

       u: An m x 'npar' x 'npar' array containing the
          variance-covariance matrices of the m complete data analyses.

    qbar: The average of complete data estimates.

    ubar: The average of the variance-covariance matrix of the complete
          data estimes.

       b: The between imputation variance-covariance matrix.

       t: The total variance-covariance matrix.

       r: Relative increases in variance due to missing data

      df: Degrees of freedom associated with the t-statistics.

       f: Fractions of missing information.

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

     Stef van Buuren, Karin Oudshoorn, 2000

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

     Van Buuren, S. & Oudshoorn, C.G.M. (2000). Multivariate Imputation
     by Chained Equations:  MICE V1.0 User's manual. Report
     PG/VGZ/00.038, TNO Prevention and Health, Leiden.

