Complementary Log-Log Regression for the Estimation of Covariate-Adjusted Prevalence Ratios in the Analysis of Data from Cross-Sectional Studies
Complementary Log-Log Regression for the Estimation of Covariate-Adjusted Prevalence Ratios in the Analysis of Data from Cross-Sectional Studies
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DOI：
10.1002/bimj.200800236
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发表时间：
2009-07-01
影响因子：
1.7
通讯作者：
Johnson, William D.
中科院分区：
文献类型：
--
作者：
Penman, Alan D.;Johnson, William D.
我们评估了互补对数-对数（CLL）回归作为估计多变量调整患病率（PR）及其置信区间的替代统计模型。使用delta方法，我们导出了近似使用CLL回归估计的PR方差的表达式。然后，利用模拟数据，我们从PR估计的准确性、置信区间的宽度和经验覆盖概率三个方面检验了CLL回归的性能，并将其与对数二项回归和分层Mantel-Haenszel分析的结果进行了比较。在我们模拟数据的值范围内，CLL回归表现良好，只有PR点估计的轻微偏差和良好的置信区间覆盖。此外，重要的是，该计算算法没有对数二项回归偶尔出现的收敛问题。该技术很容易在SAS （SAS Institute, Cary， NC）中实现，并且不存在与竞争方法相关的理论和实践问题。CLL回归是二项回归的一种替代方法，值得进一步评估。
We assessed complementary log-log (CLL) regression as an alternative statistical model for estimating multivariable-adjusted prevalence ratios (PR) and their confidence intervals. Using the delta method, we derived an expression for approximating the variance of the PR estimated using CLL regression. Then, using simulated data, we examined the performance of CLL regression in terms of the accuracy of the PR estimates, the width of the confidence intervals, and the empirical coverage probability, and compared it with results obtained from log-binomial regression and stratified Mantel-Haenszel analysis. Within the range of values of our simulated data, CLL regression performed well, with only slight bias of point estimates of the PR and good confidence interval coverage. In addition, and importantly, the computational algorithm did not have the convergence problems occasionally exhibited by log-binomial regression. The technique is easy to implement in SAS (SAS Institute, Cary, NC), and it does not have the theoretical and practical issues associated with competing approaches. CLL regression is an alternative method of binomial regression that warrants further assessment.