causalsens: Selection Bias Approach to Sensitivity Analysis for Causal Effects

The causalsens package provides functions to perform sensitivity analyses and to study how various assumptions about selection bias affects estimates of causal effects.

AuthorMatthew Blackwell <mblackwell@gov.harvard.edu.edu>
Date of publication2015-07-01 06:11:34
MaintainerMatthew Blackwell <mblackwell@gov.harvard.edu>
LicenseGPL (>= 2)
Version0.1.1
http://www.mattblackwell.org/software/causalsens/

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Files in this package

causalsens
causalsens/inst
causalsens/inst/doc
causalsens/inst/doc/causalsens.Rnw
causalsens/inst/doc/causalsens.R
causalsens/inst/doc/causalsens.pdf
causalsens/NAMESPACE
causalsens/data
causalsens/data/lalonde.psid.RData
causalsens/data/lalonde.exp.RData
causalsens/R
causalsens/R/causalsens.R
causalsens/vignettes
causalsens/vignettes/causalsens.bib
causalsens/vignettes/causalsens.Rnw
causalsens/README.md
causalsens/MD5
causalsens/build
causalsens/build/vignette.rds
causalsens/DESCRIPTION
causalsens/man
causalsens/man/one.sided.Rd causalsens/man/causalsens.Rd causalsens/man/plot.causalsens.Rd causalsens/man/lalonde.exp.Rd causalsens/man/lalonde.psid.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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