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sensitivityCalibration

A Calibrated Sensitivity Analysis for Matched Observational Studies

v0.0.1 · Dec 18, 2018 · MIT + file LICENSE

Description

Implements the calibrated sensitivity analysis approach for matched observational studies. Our sensitivity analysis framework views matched sets as drawn from a super-population. The unmeasured confounder is modeled as a random variable. We combine matching and model-based covariate-adjustment methods to estimate the treatment effect. The hypothesized unmeasured confounder enters the picture as a missing covariate. We adopt a state-of-art Expectation Maximization (EM) algorithm to handle this missing covariate problem in generalized linear models (GLMs). As our method also estimates the effect of each observed covariate on the outcome and treatment assignment, we are able to calibrate the unmeasured confounder to observed covariates. Zhang, B., Small, D. S. (2018). <arXiv:1812.00215>.

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Maintainer: ‘Bo Zhang <bozhan@wharton.upenn.edu>’

No Authors@R field in DESCRIPTION.
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  Authors@R: person(given = "Bo",
                    family = "Zhang",
                    role = c("aut", "cre"),
                    email = "bozhan@wharton.upenn.edu")
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The Description field contains
  B., Small, D. S. (2018). <arXiv:1812.00215>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
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Maintainer: ‘Bo Zhang <bozhan@wharton.upenn.edu>’

No Authors@R field in DESCRIPTION.
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  Authors@R: person(given = "Bo",
                    family = "Zhang",
                    role = c("aut", "cre"),
                    email = "bozhan@wharton.upenn.edu")
as necessary.

The Description field contains
  B., Small, D. S. (2018). <arXiv:1812.00215>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Bo Zhang <bozhan@wharton.upenn.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Bo",
                    family = "Zhang",
                    role = c("aut", "cre"),
                    email = "bozhan@wharton.upenn.edu")
as necessary.

The Description field contains
  B., Small, D. S. (2018). <arXiv:1812.00215>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Bo Zhang <bozhan@wharton.upenn.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Bo",
                    family = "Zhang",
                    role = c("aut", "cre"),
                    email = "bozhan@wharton.upenn.edu")
as necessary.

The Description field contains
  B., Small, D. S. (2018). <arXiv:1812.00215>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Dependency Network

Dependencies Reverse dependencies ggplot2 relaimpo splitstackshape ggrepel stringi plotly sensitivityCalibration

Version History

new 0.0.1 Mar 9, 2026