论文标题
Q统计量具有恒定和逆差异权重的模拟二进制效果测量的模拟
Simulations for the Q statistic with constant and inverse variance weights for binary effect measures
论文作者
论文摘要
Cochran的$ Q $统计量通常用于测试荟萃分析中的异质性。它的预期值（在不正确的空分布下）是研究间差异的几个流行估计量的一部分，即$τ^2 $。这些应用程序通常不会说明研究在定义$ q $（更明确地，$ q_ {iv} $）的反变量权重中估计方差的使用。重要的是，这些权重使$ q_ {iv} $的分布相当复杂。 作为替代方案，我们正在调查$ Q $统计量，$ q_f $，其不断的权重仅使用研究的手臂级样本量。对于log-odds-ratio，对数相对风险和风险差异作为效果的度量，这些模拟研究了$ q_f $和$ q_ {iv} $的分布的近似值，是异质性测试的基础。 我们介绍了132个数字的结果，总共153页。
Cochran's $Q$ statistic is routinely used for testing heterogeneity in meta-analysis. Its expected value (under an incorrect null distribution) is part of several popular estimators of the between-study variance, $τ^2$. Those applications generally do not account for the studies' use of estimated variances in the inverse-variance weights that define $Q$ (more explicitly, $Q_{IV}$). Importantly, those weights make approximating the distribution of $Q_{IV}$ rather complicated. As an alternative, we are investigating a $Q$ statistic, $Q_F$, whose constant weights use only the studies' arm-level sample sizes. For log-odds-ratio, log-relative-risk, and risk difference as the measure of effect, these simulations study approximations to the distributions of $Q_F$ and $Q_{IV}$, as the basis for tests of heterogeneity. We present the results in 132 Figures, 153 pages in total.
