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Henrion, Marc (2021) 'bootComb—an R package to derive confidence intervals for combinations of independent parameter estimates'. International Journal of Epidemiology, Vol 50, Issue 4, pp. 1071-1076.
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Abstract
Motivation: To address the limits of facility- or study-based estimates, multiple independent parameter estimates may need to be combined. Specific examples include (i) adjusting an incidence rate for healthcare utilisation, (ii) deriving a disease prevalence from a conditional prevalence and the prevalence of the underlying condition, (iii) adjusting a seroprevalence for test sensitivity and specificity. Calculating combined parameter estimates is generally straightforward, but deriving corresponding confidence intervals often is not. bootComb is an R package using parametric bootstrap sampling to derive such intervals.
Implementation: bootComb is a package for the statistical computation environment R.
General features: Apart from a function returning 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 for parameters given their reported confidence intervals.
| Item Type: | Article |
|---|---|
| Subjects: | W General Medicine. Health Professions > W 26.5 Informatics. Health informatics WA Public Health > Statistics. Surveys > WA 900 Public health statistics |
| Faculty: Department: | Clinical Sciences & International Health > Malawi-Liverpool-Wellcome Programme (MLW) |
| Digital Object Identifer (DOI): | https://doi.org/10.1093/ije/dyab049 |
| Depositing User: | Julie Franco |
| Date Deposited: | 08 Jun 2021 11:19 |
| Last Modified: | 10 Dec 2021 13:47 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/18055 |
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