diagnose               package:MatchIt               R Documentation

_D_i_a_g_n_o_s_t_i_c_s _f_o_r _m_a_t_c_h_i_n_g _p_r_o_c_e_d_u_r_e

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

     'diagnose' is a sub-function of 'matchit' which calculates summary
     statistics for the matching, including the weight for each unit.

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

      diagnose <- diagnose(formula, match.matrix, pscore, in.sample, data, exact=FALSE,
                     mahvars=NULL, subclass=0, psclass=NULL, nearest=TRUE, q.cut=NULL, counter=TRUE)

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

 formula: (required).  Takes the form of 'T ~ X1 + X2', where 'T' is a
          binary treatment indicator and 'X1' and 'X2' are the
          pre-treatment covariates, and 'T', 'X1', and 'X2' are
          contained in the same data frame.  The '+' symbol means
          "inclusion" not "addition." You may also include interaction
          terms in the form if 'I(X1*X2)' or squared terms in the form
          of 'I(X1^2)'.

match.matrix: (required). n1 by ratio data frame where the rows
          correspond to treated units and the columns store the names
          of the control units matched to each treated unit.  NA
          indicates that treated unit was not matched. Generally
          created in 'nearest'.

  pscore: (required). Vector of estimated propensity scores.  Generally
          calculated in 'distance'.

in.sample: (required). Vector of length n showing whether each unit was
          eligible for matching due to common support restrictions with
          'discard'.  Generally calculated in 'distance'.

    data: (required).  Data frame containing the variables called in
          the 'formula'.   The dataframe should not include variables
          with the names 'psclass', 'psweights', or 'pscore', as these
          are expressly reserved in the output dataframe for MatchIt.

   exact: "FALSE" (default)=no exact matching.  "TRUE"=exact matching
          on all variables in 'formula'.  A vector of variable names
          (that are in 'data' to indicate separate variables on which
          to exact match, in combination with matching on the
          propensity score.

 mahvars: Variables on which to perform Mahalanobis matching within
          each caliper (default=NULL).  Should be entered as a vector
          of names of variables in 'data'.

subclass: Either a scaler specifying the number of subclasses
          (default=0) or a vector of probabilities to create quantiles
          based on 'sub.by'.

 psclass: Subclass index in an ordinal scale from 1 to the number of
          subclasses.   Unmatched units have subclass=0.  Generally
          computed in 'subclassify'.

 nearest: Whether to perform nearest-neighbor matching (default=TRUE).  

   q.cut: Subclass cut points.  Generally calculated in 'subclassify'.

 counter: Whether to display counter indicating the progress of the
          matching (default=TRUE).

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

     This is a sub-function of 'matchit' which calculates summary
     statistics for the matching procedure in 'matchit', calculating
     t-statistics for covariates as well as weights for each unit. 
     This function is called directly by 'matchit' and does not
     generally need to be called directly by users; these details are
     included for advanced users.

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

psweights: Vector of length n giving the weight assigned to each unit
          in the matching process.  Each weight is proportional to the
          number of times that unit was matched.

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

     Daniel Ho <deho@fas.harvard.edu>;  Kosuke Imai
     <kimai@princeton.edu>; Gary King <king@harvard.edu>; Elizabeth
     Stuart<stuart@stat.harvard.edu>

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

     Please use 'help.matchit' to access the matchit reference manual. 
     The complete document is available online at <URL:
     http://gking.harvard.edu/matchit>.

