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?:abstract
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Motivation. The epidemiologist sometimes needs to combine several independent parameter estimates: e.g. (i) adjust an incidence rate for healthcare utilisation, (ii) derive a disease prevalence from the conditional prevalence on another condition and the prevalence of that condition, (iii) adjust a seroprevalence for test sensitivity and specificity. While obtaining the combined parameter estimate is usually straightforward, deriving a corresponding confidence interval often is not. bootComb is an R package using parametric bootstrap sampling to derive such confidence intervals. Implementation. bootComb is a package for the statistical computation environment R. General features. As well as a function that returns confidence intervals for parameters combined from several independent estimates, bootComb provides auxiliary functions for 6 common distributions (beta, normal, exponential, gamma, Poisson and negative binomial) to derive best-fit distributions (and their sampling functions) for parameters given their reported confidence intervals. Availability. bootComb is available from the Comprehensive R Archive Network (https://CRAN.R-project.org/package=bootComb).
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?:doi
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?:doi
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10.1101/2020.12.01.20241919
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?:title
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bootComb - An R Package to Derive Confidence Intervals for Combinations of Independent Parameter Estimates
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