help imb

Title

cem -- Measure of (Im)balance for CEM

Syntax

imb varlist [if] [in] [, options]

options

treatment(varname) name of the treatment variable

breaks(string) method used to generate cutpoints

miname(string) filename root of the imputed datasets, if in separate files

misets(integer) number of imputed datasets, if in separate files

impvar(string) name of imputed dataset variable, if in stack/flong format

useweights should the cem_weights be use?

Description

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 breaks and comparing across the
multivariate histogram. See Iacus, King and Porro (2008) for more details
on this measure.

Arguments

Main

varlist is a list of variables to be included as coviarates.

Options

treatment(varname) sets the treatment variable used for the imbalance
checks. Note that imb will use the highest value of this variable as
the "treated" category.

breaks(string) sets the default automatic coarsening
algorithm. If either cem or imb has been run and there
is a 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.

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 miname were
"imputed", then the filenames should be "imputed1.dta","imputed2.dta"
and so on.

misets(integer) if the imputed datasets are in separate
files, is the number of imputed datasets being used for matching.

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.

useweights makes imb use the weights from the output of cem. This is useful for checking balance after running cem.

Saved Results

Scalars

r(L1) multivariate imbalance measure

Matrices

r(imbal) matrix of univariate imbalance measures

Strings

r(L1_breaks) break method used for L1 distance

References and Distribution

cem is licensed under GLP2. For more information, see: http://gking.harvard.edu/cem/

For a full reference on Coarsened Exact Matching, see:

Stefano M. Iacus, Gary King, and Giuseppe Porro, "Matching for Causal
Inference Without Balance Checking", copy at
<http://gking.harvard.edu/files/abs/cem-abs.shtml>

To report bugs or give comments, please contact Matthew Blackwell
<blackwel@fas.harvard.edu>.