bootComb—an R package to derive confidence intervals for combinations of independent parameter estimates

bootComb—an R package to derive confidence intervals for combinations of independent parameter estimates
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DOI:
10.1093/ije/dyab049
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发表时间:
2021-05-19
影响因子:
7.7
通讯作者:
Henrion MY
Henrion MY
中科院分区:
医学1区
文献类型:
--
作者:
Henrion MY

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为了解决基于设施或基于研究的估计的局限性,可能需要组合多个独立参数估计。具体示例包括(i)调整医疗保健利用的发病率,(ii)从条件患病率和基础疾病的患病率推导出疾病患病率,(iii)调整测试敏感性和特异性的血清患病率。计算组合参数估计值通常很简单,但推导相应的置信区间通常并非如此。 bootComb 是一个 R 包,使用参数引导采样来导出此类间隔。 bootComb 是统计计算环境 R 的软件包。除了返回由多个独立估计组合的参数的置信区间的函数外,bootComb 还提供 6 种常见分布(β、正态、指数、伽马、泊松和负二项式)的辅助函数,以便在给定报告的置信区间的情况下导出参数的最佳拟合分布。 bootComb 可从综合 R 存档网络 (https://CRAN.R-project.org/package=bootComb) 获取。
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. bootComb is a package for the statistical computation environment R. 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. bootComb is available from the Comprehensive R Archive Network (https://CRAN.R-project.org/package=bootComb).
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