The use of Linear Mixed-effects Models (LMMs) is set to dominate statistical analyses in psychological science and may become the default approach to analyzing quantitative data. The rapid growth in adoption of LMMs has been matched by a proliferation of differences in practice. Unless this diversity is recognized, and checked, the field shall reap enormous difficulties in the future when attempts are made to consolidate or synthesize research findings. Here we examine this diversity using two methods – a survey of researchers (n=163) and a quasi-systematic review of papers using LMMs (n=400). The survey reveals substantive concerns among psychologists using or planning to use LMMs and an absence of agreed standards. The review of papers complements the survey, showing variation in how the models are built, how effects are evaluated and, most worryingly, how models are reported. Using these data as our departure point, we present a set of best practice guidance, focusing on the reporting of LMMs. It is the authors’ intention that the paper supports a step-change in the reporting of LMMs across the psychological sciences, preventing a trajectory in which findings reported today cannot be transparently understood and used tomorrow.

中文翻译：

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心理科学中线性混合效应模型的最佳实践指南

线性混合效应模型 (LMM) 的使用将主导心理科学的统计分析，并可能成为分析定量数据的默认方法。LMM 采用的快速增长与实践中差异的激增相匹配。除非这种多样性得到承认和检查，否则该领域将来在试图巩固或综合研究成果时将面临巨大的困难。在这里，我们使用两种方法检查这种多样性——研究人员调查 (n=163) 和使用 LMM 的论文准系统审查 (n=400)。调查揭示了心理学家使用或计划使用 LMM 以及缺乏商定标准的实质性担忧。论文审查补充了调查，显示了模型构建方式、效果评估方式以及，最令人担忧的是，模型是如何报告的。使用这些数据作为我们的出发点，我们提出了一套最佳实践指南，重点是 LMM 的报告。作者的意图是该论文支持跨心理科学的 LMM 报告的阶跃变化，防止今天报告的结果无法在明天被透明地理解和使用的轨迹。