exact2x2-package: Exact Tests and Confidence Intervals for 2x2 Tables

Description Details Author(s) References

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: 1.6.6
Date: 2021-12-08
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 Dec. 11, 2021, 9:43 a.m.