Six solutions for more reliable infant research

Infant research is often underpowered, undermining the robustness and replicability of our findings. Improving the reliability of infant studies offers a solution for increasing statistical power independent of sample size. Here, we discuss two senses of the term reliability in the context of infant research: reliable (large) effects and reliable measures. We examine the circumstances under which effects are strongest and measures are most reliable, and use synthetic datasets to illustrate the relationship between effect size, measurement reliability, and statistical power. We then present six concrete solutions for more reliable infant research: (1) routinely estimating and reporting the effect size and measurement reliability of infant tasks, (2) selecting the best measurement tool, (3) developing better infant paradigms, (4) collecting more data points per infant, (5) excluding unreliable data from analysis, and (6) conducting more sophisticated data analyses. Deeper consideration of measurement in infant research will improve our ability to study infant development.

婴幼儿研究常因样本量不足而削弱其结果的稳健性和可重复性。提升婴幼儿研究的可靠性，为独立于样本大小增加统计功效提供了一种解决方案。在此，我们探讨婴幼儿研究语境下“可靠性”这一术语的两种含义：可靠（显著）效应与可靠测量。我们分析了效应最强和测量最可靠的情境，并利用合成数据集展示了效应量、测量可靠性与统计功效之间的关系。随后，我们提出了六项具体策略以增强婴幼儿研究的可靠性：（1）常规估算并报告婴幼儿任务的效应量和测量可靠性，（2）选择最佳测量工具，（3）开发更优的婴幼儿实验范式，（4）增加每个婴幼儿的数据点收集量，（5）排除分析中的不可靠数据，（6）进行更复杂的数据分析。对婴幼儿研究中测量的深入思考将提升我们研究婴幼儿发展的能力。