论文标题
估计异质性方差的仿真$τ^2 $在恒定和反向差异权重的log-odds-ratios的荟萃分析
Simulations for estimation of heterogeneity variance $τ^2$ in constant and inverse variance weights meta-analysis of log-odds-ratios
论文作者
论文摘要
研究间差异的许多流行估计器，$τ^2 $，基于Cochran的$ Q $统计量，用于测试元分析中的异质性。我们为log-odds-ratio介绍了$τ^2 $的新点和间隔估计器。其中包括基于$ q_f $的第一时刻，具有有效样本大小的重量的$ q $统计量以及新颖的中值估计器的新型Dersimonian-kacker型力矩估计器。 We study, by simulation, bias and coverage of these new estimators of $τ^2$ and, for comparative purposes, bias and coverage of a number of well-known estimators based on the $Q$ statistic with inverse-variance weights, $Q_{IV}$, such as the Mandel-Paule, DerSimonian-Laird, and restricted-maximum-likelihood estimators, and an estimator based on the Kulinskaya-Dollinger（2015）将近似值提高到$ q_ {iv} $。
A number of popular estimators of the between-study variance, $τ^2$, are based on the Cochran's $Q$ statistic for testing heterogeneity in meta analysis. We introduce new point and interval estimators of $τ^2$ for log-odds-ratio. These include new DerSimonian-Kacker-type moment estimators based on the first moment of $Q_F$, the $Q$ statistic with effective-sample-size weights, and novel median-unbiased estimators. We study, by simulation, bias and coverage of these new estimators of $τ^2$ and, for comparative purposes, bias and coverage of a number of well-known estimators based on the $Q$ statistic with inverse-variance weights, $Q_{IV}$, such as the Mandel-Paule, DerSimonian-Laird, and restricted-maximum-likelihood estimators, and an estimator based on the Kulinskaya-Dollinger (2015) improved approximation to $Q_{IV}$.
