balanceUV              package:Matching              R Documentation

_U_n_i_v_a_r_i_a_t_e _B_a_l_a_n_c_e _T_e_s_t_s

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

     This function provides a number of univariate balance tests.
     Generally, users should call 'MatchBalance' and not this function
     directly.

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

     balanceUV(Tr, Co, weights = rep(1, length(Co)), exact = FALSE, ks=FALSE,
               nboots = 1000, paired=TRUE, match=FALSE,
               weights.Tr=rep(1,length(Tr)), weights.Co=rep(1,length(Co)))

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

      Tr: A vector containing the treatment observations.

      Co: A vector containing the control observations.

 weights: A vector containing the observation specific weights. Only
          use this option when the treatment and control observations
          are paired (as they are after matching).

   exact: A logical flag indicating if the exact Wilcoxon test should
          be used instead of the test with a correction.  See
          'wilcox.test' for details.

      ks: A logical flag for if the univariate bootstrap
          Kolmogorov-Smirnov (KS) test should be calculated.  If the ks
          option is set to true, the univariate KS test is calculated
          for all non-dichotomous variables.  The bootstrap KS test is
          consistent even for non-continuous variables.  See 'ks.boot'
          for more details.

  nboots: The number of bootstrap samples to be run for the 'ks' test. 
          If zero, no bootstraps are done.  Bootstrapping is highly
          recommended because the bootstrapped Kolmogorov-Smirnov test
          only provides correct coverage even for non-continuous
          covariates. At least 500 'nboots' (preferably 1000) are
          recommended for publication quality p-values.

  paired: A flag for if the paired 't.test' should be used.

   match: A flag for if the 'Tr' and 'Co' objects are the result of a
          call to 'Match'.

weights.Tr: A vector of weights for the treated observations.

weights.Co: A vector of weights for the control observations.

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

   sdiff: This is the standardized difference which is the mean
          difference between treatment and control divided by the
          square root of the average variance (of treatment and
          control).  The entire quantity is then multiplied by a 100.

 mean.Tr: The mean of the treatment group.

 mean.Co: The mean of the control group.

  var.Tr: The variance of the treatment group.

  var.Co: The variance of the control group.

 p.value: The p-value from the two-sided weighted 't.test'.

var.ratio: var.Tr/var.Co.

      ks: The object returned by 'ks.boot'.

      tt: The object returned by two-sided weighted 't.test'.

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

     Jasjeet S. Sekhon, Harvard University, jasjeet_sekhon@harvard.edu,
     <URL: http://jsekhon.fas.harvard.edu/>

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

     Hollander, Myles and Douglas A. Wolfe. 1973. _Nonparametric
     statistical inference_. New York: John Wiley & Sons.

     Sekhon, Jasjeet S. 2004.  ``Balance Tests for Matching
     Estimators.''  Working Paper.

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

     Also see 'summary.balanceUV', 'ks.boot', 'Match', 'GenMatch',
     'MatchBalance', 'balanceMV', 'GerberGreenImai', 'lalonde'

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

     data(lalonde)
     attach(lalonde)

     foo  <- balanceUV(re75[treat==1],re75[treat!=1])
     summary(foo)

