exact2x2-package: Exact Tests and Confidence Intervals for 2x2 Tables
In exact2x2: Exact Tests and Confidence Intervals for 2x2 Tables
exact2x2-package R Documentation
Exact Tests and Confidence Intervals for 2x2 Tables
Description
There are 8 main functions in the package.
The exact2x2 function calculates the exact conditional tests with matching confidence intervals as detailed in Fay (2010a <DOI:10.1093/biostatistics/kxp050>,2010b). The functions ss2x2 and power2x2 calculate the sample size and power related to the tests of exact2x2. The uncondExact2x2
and boschloo functions calculate unconditional exact tests (see Fay and Hunsberger, 2021, <DOI:10.1214/21-SS131>).
The binomMeld.test function calculates melded confidence intervals for two sample binomial inferences (see Fay, Proschan, and Brittain, 2015 <DOI:10.1111/biom.12231>).
Finally, the borrTest function calculates the boundary optimized rejection region test that
creates unconditional exact tests that have power optimized when group 1 is expected to have 100 percent failure. For example, in vaccine challenge studies where the control group are all expected to get infected (see Gabriel, et al, 2018 <DOI:10.1002/sim.7579>, the letter about that paper by Martin Andres <DOI:10.1002/sim.7630>, and the response <DOI:10.1002/sim.7684>). The mcnemarExactDP function give p-values and confidence intervals compatible with exact McNemar's or sign tests (Fay and Lumbard, 2021, <DOI:10.1002/sim.8829>).
Details
Package: bpcp
Type: Package
Version: 1.7.0
Date: 2025-08-20
License: GPL3
LazyLoad: yes
Author(s)
Michael P. Fay, Sally A. Hunsberger, Martha Nason, Erin Gabriel, Keith Lumbard
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>
References
Fay, M. P. (2010a). Confidence intervals that Match Fisher's exact and Blaker's exact tests. Biostatistics,
11: 373-374 (go to doc directory for earlier version or
https://www.niaid.nih.gov/about/brb-staff-fay for link to official version).
Fay, M.P. (2010b). Two-sided Exact Tests and Matching Confidence Intervals for Discrete Data. R Journal 2(1):53-58.
Fay, M.P. and Hunsberger, S.A. (2021). Practical Valid Inferences for the Two-Sample Binomial Problem. Statistics Surveys 15:72-110.
Fay, MP, Proschan, MA, and Brittain, E (2015). Combining One Sample Confidence Procedures for Inference in the Two Sample Case. Biometrics. 71: 146-156.
Gabriel, EE, Nason, M, Fay, MP, and Follmann, DA. (2018). A boundary-optimized rejection region test for the two-sample binomial problem. Statistics in Medicine. 37(7): 1047-1058 (DOI: 10.1002/sim.7579).
Gabriel, EE, Nason, M, Fay, MP, and Follmann, DA. (2018). Reply to letter from Martin Andres. Statistics in Medicine 37(14): 2303-2306.
Martin Andres, Antonio. (2018). Letter to the editor about Gabriel et al. Statistics in Medicine 37(14) 2301-2302.
exact2x2 documentation built on Aug. 21, 2025, 5:59 p.m.
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| exact2x2-package | R Documentation |
Exact Tests and Confidence Intervals for 2x2 Tables
Description
There are 8 main functions in the package.
The exact2x2 function calculates the exact conditional tests with matching confidence intervals as detailed in Fay (2010a <DOI:10.1093/biostatistics/kxp050>,2010b). The functions ss2x2 and power2x2 calculate the sample size and power related to the tests of exact2x2. The uncondExact2x2
and boschloo functions calculate unconditional exact tests (see Fay and Hunsberger, 2021, <DOI:10.1214/21-SS131>).
The binomMeld.test function calculates melded confidence intervals for two sample binomial inferences (see Fay, Proschan, and Brittain, 2015 <DOI:10.1111/biom.12231>).
Finally, the borrTest function calculates the boundary optimized rejection region test that
creates unconditional exact tests that have power optimized when group 1 is expected to have 100 percent failure. For example, in vaccine challenge studies where the control group are all expected to get infected (see Gabriel, et al, 2018 <DOI:10.1002/sim.7579>, the letter about that paper by Martin Andres <DOI:10.1002/sim.7630>, and the response <DOI:10.1002/sim.7684>). The mcnemarExactDP function give p-values and confidence intervals compatible with exact McNemar's or sign tests (Fay and Lumbard, 2021, <DOI:10.1002/sim.8829>).
Details
| Package: | bpcp |
| Type: | Package |
| Version: | 1.7.0 |
| Date: | 2025-08-20 |
| License: | GPL3 |
| LazyLoad: | yes |
Author(s)
Michael P. Fay, Sally A. Hunsberger, Martha Nason, Erin Gabriel, Keith Lumbard
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>
References
Fay, M. P. (2010a). Confidence intervals that Match Fisher's exact and Blaker's exact tests. Biostatistics, 11: 373-374 (go to doc directory for earlier version or https://www.niaid.nih.gov/about/brb-staff-fay for link to official version).
Fay, M.P. (2010b). Two-sided Exact Tests and Matching Confidence Intervals for Discrete Data. R Journal 2(1):53-58.
Fay, M.P. and Hunsberger, S.A. (2021). Practical Valid Inferences for the Two-Sample Binomial Problem. Statistics Surveys 15:72-110.
Fay, MP, Proschan, MA, and Brittain, E (2015). Combining One Sample Confidence Procedures for Inference in the Two Sample Case. Biometrics. 71: 146-156.
Gabriel, EE, Nason, M, Fay, MP, and Follmann, DA. (2018). A boundary-optimized rejection region test for the two-sample binomial problem. Statistics in Medicine. 37(7): 1047-1058 (DOI: 10.1002/sim.7579).
Gabriel, EE, Nason, M, Fay, MP, and Follmann, DA. (2018). Reply to letter from Martin Andres. Statistics in Medicine 37(14): 2303-2306.
Martin Andres, Antonio. (2018). Letter to the editor about Gabriel et al. Statistics in Medicine 37(14) 2301-2302.
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