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dstat  

Conditional Sensitivity Analysis for Matched Observational Studies
View on CRAN: Click here


Download and install dstat package within the R console
Install from CRAN:
install.packages("dstat")

Install from Github:
library("remotes")
install_github("cran/dstat")

Install by package version:
library("remotes")
install_version("dstat", "1.0.4")



Attach the package and use:
library("dstat")
Maintained by
Paul R. Rosenbaum
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-04-16
Latest Update: 2019-04-16
Description:
A d-statistic tests the null hypothesis of no treatment effect in a matched, nonrandomized study of the effects caused by treatments. A d-statistic focuses on subsets of matched pairs that demonstrate insensitivity to unmeasured bias in such an observational study, correcting for double-use of the data by conditional inference. This conditional inference can, in favorable circumstances, substantially increase the power of a sensitivity analysis (Rosenbaum (2010) ). There are two examples, one concerning unemployment from Lalive et al. (2006) , the other concerning smoking and periodontal disease from Rosenbaum (2017) .
How to cite:
Paul R. Rosenbaum (2019). dstat: Conditional Sensitivity Analysis for Matched Observational Studies. R package version 1.0.4, https://cran.r-project.org/web/packages/dstat
Previous versions and publish date:
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Functions, R codes and Examples using the dstat R package
Some associated functions: amplify . dental . dstat-package . dstat . lalive . 
Some associated R codes: amplify.R . dstat.R .  Full dstat package functions and examples
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