dstat: Conditional Sensitivity Analysis for Matched Observational
Studies
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) <doi:10.1007/978-1-4419-1213-8_14>). There are two examples, one concerning unemployment from Lalive et al. (2006) <doi:10.1111/j.1467-937X.2006.00406.x>, the other concerning smoking and periodontal disease from Rosenbaum (2017) <doi:10.1214/17-STS621>.
| Version: |
1.0.4 |
| Imports: |
stats |
| Published: |
2019-04-16 |
| Author: |
Paul R. Rosenbaum |
| Maintainer: |
Paul R. Rosenbaum <rosenbaum at wharton.upenn.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| In views: |
CausalInference |
| CRAN checks: |
dstat results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=dstat
to link to this page.