pstest: Specification Tests for Parametric Propensity Score Models

The propensity score is one of the most widely used tools in studying the causal effect of a treatment, intervention, or policy. Given that the propensity score is usually unknown, it has to be estimated, implying that the reliability of many treatment effect estimators depends on the correct specification of the (parametric) propensity score. This package implements the data-driven nonparametric diagnostic tools for detecting propensity score misspecification proposed by Sant'Anna and Song (2019) <doi:10.1016/j.jeconom.2019.02.002>.

Version:	0.1.3.900
Depends:	R (≥ 3.1)
Imports:	stats, parallel, glmx, MASS, utils
Published:	2019-08-26
Author:	Pedro H. C. Sant'Anna, Xiaojun Song
Maintainer:	Pedro H. C. Sant'Anna <pedro.h.santanna at vanderbilt.edu>
License:	GPL-2
URL:	https://github.com/pedrohcgs/pstest
NeedsCompilation:	no
Materials:	README
CRAN checks:	pstest results

Documentation:

Reference manual:

pstest.pdf

Downloads:

Package source:	pstest_0.1.3.900.tar.gz
Windows binaries:	r-devel: pstest_0.1.3.900.zip, r-release: pstest_0.1.3.900.zip, r-oldrel: pstest_0.1.3.900.zip
macOS binaries:	r-release (arm64): pstest_0.1.3.900.tgz, r-oldrel (arm64): pstest_0.1.3.900.tgz, r-release (x86_64): pstest_0.1.3.900.tgz, r-oldrel (x86_64): pstest_0.1.3.900.tgz
Old sources:	pstest archive

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