Adjusting Published Estimates for Exploratory Biases Using the Truncated Normal Distribution

<i>Abstract–</i>Publication bias can occur for many reasons, including the perceived need to present statistically significant results. We propose and compare methods for adjusting a single published estimate for possible publication bias using a truncated normal distribution. We attempt to estimate the mean of the underlying normal sampling distribution using only summary data readily available in most published work, making the results practical for use by a consumer of research. The adjustment methods are investigated via simulation and their results compared in terms of bias, mean squared error, and confidence interval coverage. The methods are also applied to eleven previously published studies. We find the proposed methods improve but do not eliminate biases from the statistical significance filter.

摘要——
发表偏倚（publication bias）的成因多种多样，其中包括研究者为呈现具有统计学显著性的结果而产生的主观诉求。本研究提出并对比了多种基于截尾正态分布（truncated normal distribution）的校正方法，用于校正单篇已发表文献中的估计值以应对潜在发表偏倚。本研究仅借助多数已发表文献中均可便捷获取的汇总数据（summary data），对潜在正态抽样分布的均值进行估计，使得研究结果具备实用性，可供科研使用者直接应用。本研究通过模拟实验对上述校正方法开展验证，并从偏倚、均方误差（mean squared error）以及置信区间覆盖率（confidence interval coverage）三个维度对其结果进行对比分析。此外，本研究将所提方法应用于11项既往已发表的研究。研究结果表明，本研究提出的方法可改善但无法完全消除由统计学显著性筛选所带来的偏倚。