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cem

Authors: Stefano Iacus, Gary King, Giuseppe Porro

This R package is designed to improve the estimation of causal effects via an extremely powerful method of matching that is widely applicable and exceptionally easy to understand and use (if you understand how to draw a histogram, you will understand this method). The program implements the Coarsened Exact Matching (CEM) algorithm described in:

Stefano M. Iacus, Gary King, and Giuseppe Porro, "Causal Inference Without Balance Checking: Coarsened Exact Matching"

and " Multivariate Matching Methods That are Monotonic Imbalance Bounding ".

For more information, see package website at:

http://gking.harvard.edu/cem

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Version

Install

install.packages('cem')

Monthly Downloads

1,789

Version

1.1.31

License

GPL-2

Last Published

September 8th, 2022

Functions in cem (1.1.31)

L1.meas

Evaluates L1 distance between multidimensional histograms
LL

Lalonde dataset
L1.profile

Calculates L1 distance for different coarsenings
cemspace

Exploration tool for CEM
shift.cem

Diagnostic tool for CEM
combine.spacegraphs

Combine two spacegraph objects.
imbspace.plot

Plot of imbalance space diagnostic tool for CEM
att

Example of ATT estimation from CEM output
cem

Coarsened Exact Matching
k2k

Reduction to k2k Matching
imbalance

Calculates several imbalance measures
imbspace

Diagnostic tool for CEM
relax.cem

Diagnostic tool for CEM
pair

Produces a paired sample out of a CEM match solution
pscoreSelect

Heuristic search of the best propensity score model specification
spacegraph

Randomly compute many different matching solutions
search.match

Heuristic search of match solutions
LeLonde

Modified Lalonde dataset
LLvsPSID

Lalonde treated units versus PSID control individuals
DW

Dehejia-Wahba dataset