MIcombine              package:mitools              R Documentation

_M_u_l_t_i_p_l_e _i_m_p_u_t_a_t_i_o_n _i_n_f_e_r_e_n_c_e

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

     Combines results of analyses on multiply imputed data sets. A
     generic function with methods for 'imputationResultList' objects
     and a default method.  In addition to point estimates and
     variances, 'MIcombine' computes Rubin's degrees-of-freedom
     estimate and rate of missing information.

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

     MIcombine(results, ...)
     ## Default S3 method:
     MIcombine(results,variances,call=sys.call(),...)
     ## S3 method for class 'imputationResultList':
     MIcombine(results,call=NULL,...)

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

 results: A list of results from inference on separate imputed datasets

variances: If 'results' is a list of parameter vectors, 'variances'
          should be the corresponding variance-covariance matrices

    call: A function call for labelling the results

     ...: Other arguments, not used

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

     The 'results' argument in the default method may be either a list
     of parameter vectors or a list of objects that have 'coef' and
     'vcov' methods.  In the former case a list of variance-covariance
     matrices must be supplied as the second argument.

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

     An object of class 'MIresult' with 'summary' and 'print' methods

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

     ~put references to the literature/web site here ~

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

     'MIextract', 'with.imputationList'

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

     data(smi)
     models<-with(smi, glm(drinkreg~wave*sex,family=binomial()))
     summary(MIcombine(models))

     betas<-MIextract(models,fun=coef)
     vars<-MIextract(models, fun=vcov)
     summary(MIcombine(betas,vars))

