{smcl} {cmd:help imb} {hline} {title:Title} {p2colset 5 12 14 2}{...} {p2col:{hi:cem} {hline 2}}Measure of (Im)balance for CEM{p_end} {p2colreset}{...} {title:Syntax} {p 8 14 2} {opt imb} {it:varlist} {ifin} [{cmd:,} {it:options}] {synoptset 20 tabbed}{...} {marker options}{...} {synopthdr :options} {synoptline} {synopt :{opth tr:eatment(varname)}}name of the treatment variable{p_end} {synopt :{opt breaks(string)}}method used to generate cutpoints{p_end} {synopt :{opt miname(string)}}filename root of the imputed datasets, if in separate files{p_end} {synopt :{opt misets(integer)}}number of imputed datasets, if in separate files{p_end} {synopt :{opt impvar(string)}}name of imputed dataset variable, if in stack/flong format{p_end} {synopt :{opt use:weights }}should the cem_weights be use?{p_end} {title:Description} {pstd} {cmd:imb} returns a number of measures of imbalance in covariates between treatment and control groups. A multivariate L1 distance, univariate L1 distrances, difference in means and empirical quatiles difference are reported. The L1 measures are computed by coarsening the data according to {cmd:breaks} and comparing across the multivariate histogram. See Iacus, King and Porro (2008) for more details on this measure. {title:Arguments} {dlgtab:Main} {phang} {it:varlist} is a list of variables to be included as coviarates. {dlgtab:Options} {phang} {it:treatment(varname)} sets the treatment variable used for the imbalance checks. Note that {cmd:imb} will use the highest value of this variable as the "treated" category. {phang} {it:breaks(string)} sets the default automatic coarsening algorithm. If either {cmd:cem} or {cmd:imb} has been run and there is a {cmd:r(L1_breaks)} available, this will be the default. Otherwise, the default for this is "scott". It is not incredibly important which method is used here as long as it is consistent. {phang} {it:miname(string)} if the imputed datasets are in separate files, is the root of the filenames of the imputed dataset. They should be in the working directory. For example, if {cmd:miname} were "imputed", then the filenames should be "imputed1.dta","imputed2.dta" and so on. {phang} {it:misets(integer)} if the imputed datasets are in separate files, is the number of imputed datasets being used for matching. {phang} {it:impvar(string)} if the imputed data is stacked in one dataset (the Stata default), this is the name of the variable identifying to which imputation the observation belongs. {phang} {it:useweights} makes {cmd:imb} use the weights from the output of {cmd:cem}. This is useful for checking balance after running {cmd:cem}. {title:Saved Results} {synoptset 15 tabbed}{...} {p2col 5 15 19 2: Scalars}{p_end} {synopt:{cmd:r(L1)}} multivariate imbalance measure{p_end} {p2col 5 15 19 2: Matrices}{p_end} {synopt:{cmd:r(imbal)}} matrix of univariate imbalance measures{p_end} {p2col 5 15 19 2: Strings}{p_end} {synopt:{cmd:r(L1_breaks)}} break method used for L1 distance{p_end} {title:References and Distribution} {pstd} {cmd:cem} is licensed under GLP2. For more information, see: http://gking.harvard.edu/cem/ {pstd} For a full reference on Coarsened Exact Matching, see: {phang} Stefano M. Iacus, Gary King, and Giuseppe Porro, "Matching for Causal Inference Without Balance Checking", copy at {pstd} To report bugs or give comments, please contact Matthew Blackwell .