Optimising a coordinate ascent algorithm for the meta-analysis of test accuracy studies
Optimising a coordinate ascent algorithm for the meta-analysis of test accuracy studies
复制标题
优化坐标上升算法以进行测试精度研究的荟萃分析
DOI：
10.1101/2022.12.05.519131
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Baragilly M
中科院分区：
文献类型：
--
作者：
Baragilly M
荟萃分析可用于总结测试的准确性。通常，敏感性和特异性是感兴趣的度量，并且由于它们是相关的，因此通常使用二元随机效应模型来拟合数据。该模型有五个参数，并且可以使用基于 Newton-Raphson 的算法进行优化，前提是识别出足够的参数初始值。数值方法可用于估计稳健的初始值，但估计这些初始值的计算量很大，并且尚不清楚它们在减少偏差、均方误差、平均相对误差和覆盖概率方面是否比封闭形式方法具有显着优势。在这里，我们考虑六种封闭形式的方法来估计用于拟合双变量模型的坐标上升算法的参数初始值，并将它们与数值导出的稳健初始值进行比较。通过模拟研究，我们证明，与稳健的初始值方法相比，所有封闭式方法均可将计算时间减少约 80%，并且在指标中总体排名更高。尽管没有任何初始值估计器在所有参数和指标中主导其他估计器，但两步 Hedges-Olkin 估计器在不同场景中总体排名最高。
Meta-analysis may be used to summarise a test’s accuracy. Often the sensitivity and specificity are the measures of interest and as these are correlated a bivariate random effects model is commonly used to fit the data. This model has five parameters and it may be optimised using a Newton-Raphson based algorithm providing adequate initial values of the parameters are identified. Numerical methods may be used to estimate robust initial values but estimating these is computationally expensive and it is not clear whether they provide a significant advantage over closed form methods in terms of reducing bias, mean square error, average relative error, and coverage probability. Here we consider six closed form methods for estimating the initial values of the parameters for a co-ordinate ascent algorithm used to fit the bivariate model and compare them with numerically derived robust initial values. Using simulation studies we demonstrate that all the closed form methods lead to a reduction in computation time of around 80% and rank higher overall across the metrics when compared with the robust initial values method. Although no initial values estimator dominated the others across all parameters and metrics, the two-step Hedges-Olkin estimator ranked highest overall across the different scenarios.
影响因子：
--
作者：
D. Sackett;R. Haynes
通讯作者：
R. Haynes
DOI：
10.1016/0197-2456(86)90046-2
发表时间：
1986-09-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
DERSIMONIAN, R;LAIRD, N
通讯作者：
LAIRD, N
影响因子：
5
作者：
Cole, Stephen R.;Chu, Haitao;Greenland, Sander
通讯作者：
Greenland, Sander