Department of Statistics, Florida State University, Tallahassee, United States of America.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, United States of America.
J Evid Based Dent Pract. 2023 Mar;23(1):101830. doi: 10.1016/j.jebdp.2022.101830. Epub 2022 Dec 24.
Studies with statistically significant results are frequently more likely to be published than those with non-significant results. This phenomenon leads to publication bias or small-study effects and can seriously affect the validity of the conclusion from systematic reviews and meta-analyses. Small-study effects typically appear in a specific direction, depending on whether the outcome of interest is beneficial or harmful, but this direction is rarely taken into account in conventional methods.
We propose to use directional tests to assess potential small-study effects. The tests are built on a one-sided testing framework based on the existing Egger's regression test. We performed simulation studies to compare the proposed one-sided regression tests, conventional two-sided regression tests, as well as two other competitive methods (Begg's rank test and the trim-and-fill method). Their performance was measured by type I error rates and statistical power. Three real-world meta-analyses on measurements of infrabony periodontal defects were also used to examine the various methods' performance.
Based on simulation studies, the one-sided tests could have considerably higher statistical power than competing methods, particularly their two-sided counterparts. Their type I error rates were generally controlled well. In the case study of the three real-world meta-analyses, by accounting for the favored direction of effects, the one-sided tests could rule out potential false-positive conclusions about small-study effects. They also are more powerful in assessing small-study effects than the conventional two-sided tests when true small-study effects likely exist.
We recommend researchers incorporate the potential favored direction of effects into the assessment of small-study effects.
具有统计学显著结果的研究比无显著结果的研究更有可能被发表。这种现象导致了发表偏倚或小样本研究效应,可能严重影响系统评价和荟萃分析结论的有效性。小样本研究效应通常会出现在特定的方向,这取决于感兴趣的结果是有益还是有害,但在常规方法中很少考虑到这种方向。
我们建议使用定向检验来评估潜在的小样本研究效应。这些检验建立在基于现有 Egger 回归检验的单侧检验框架上。我们进行了模拟研究,比较了所提出的单侧回归检验、传统的双侧回归检验以及另外两种竞争方法(Begg 秩检验和填充法)。通过测量 I 型错误率和统计功效来评估它们的性能。还使用了三个关于骨下牙周缺损测量的真实世界荟萃分析来检验各种方法的性能。
基于模拟研究,单侧检验可能比竞争方法具有更高的统计功效,尤其是它们的双侧对应方法。它们的 I 型错误率通常得到很好的控制。在三个真实世界荟萃分析的案例研究中,通过考虑效应的有利方向,单侧检验可以排除关于小样本研究效应的潜在假阳性结论。当真正的小样本研究效应可能存在时,它们在评估小样本研究效应方面比传统的双侧检验更有功效。
我们建议研究人员将潜在的有利效应方向纳入小样本研究效应的评估中。