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r-ratesci

Anaconda Verified

Computes confidence intervals for the rate (or risk) difference ('RD') or rate ratio (or relative risk, 'RR') for binomial proportions or Poisson rates, or for odds ratio ('OR', binomial only). Also confidence intervals for a single binomial or Poisson rate, and intervals for matched pairs. Includes skewness-corrected asymptotic score ('SCAS') methods, which have been developed in Laud (2017) <doi:10.1002/pst.1813> from Miettinen & Nurminen (1985) <doi:10.1002/sim.4780040211> and Gart & Nam (1988) <doi:10.2307/2531848>. The same score produces hypothesis tests analogous to the test for binomial RD and RR by Farrington & Manning (1990) <doi:10.1002/sim.4780091208>. The package also includes MOVER methods (Method Of Variance Estimates Recovery) for all contrasts, derived from the Newcombe method but using equal-tailed Jeffreys intervals, and generalised for Bayesian applications incorporating prior information. So-called 'exact' methods for strictly conservative coverage are approximated using continuity corrections. Also includes methods for stratified calculations (e.g. meta-analysis), either assuming fixed effects (matching the CMH test) or incorporating stratum heterogeneity.

Installation

To install this package, run one of the following:

Conda
$conda install r::r-ratesci

Usage Tracking

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About

Summary

Computes confidence intervals for the rate (or risk) difference ('RD') or rate ratio (or relative risk, 'RR') for binomial proportions or Poisson rates, or for odds ratio ('OR', binomial only). Also confidence intervals for a single binomial or Poisson rate, and intervals for matched pairs. Includes skewness-corrected asymptotic score ('SCAS') methods, which have been developed in Laud (2017) <doi:10.1002/pst.1813> from Miettinen & Nurminen (1985) <doi:10.1002/sim.4780040211> and Gart & Nam (1988) <doi:10.2307/2531848>. The same score produces hypothesis tests analogous to the test for binomial RD and RR by Farrington & Manning (1990) <doi:10.1002/sim.4780091208>. The package also includes MOVER methods (Method Of Variance Estimates Recovery) for all contrasts, derived from the Newcombe method but using equal-tailed Jeffreys intervals, and generalised for Bayesian applications incorporating prior information. So-called 'exact' methods for strictly conservative coverage are approximated using continuity corrections. Also includes methods for stratified calculations (e.g. meta-analysis), either assuming fixed effects (matching the CMH test) or incorporating stratum heterogeneity.

Last Updated

Jun 27, 2022 at 20:09

License

GPL-3

Supported Platforms

noarch