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: (a) routinely estimating and reporting the effect size and measurement reliability of infant tasks, (b) selecting the best measurement tool, (c) developing better infant paradigms, (d) collecting more data points per infant, (e) excluding unreliable data from the analysis, and (f) conducting more sophisticated data analyses. Deeper consideration of measurement in infant research will improve our ability to study infant development.

中文翻译：

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六种解决方案让婴儿研究更可靠

婴儿研究通常动力不足，破坏了我们研究结果的稳健性和可重复性。提高婴儿研究的可靠性为增加独立于样本量的统计功效提供了解决方案。在这里，我们讨论了婴儿研究背景下可靠性一词的两种含义：可靠（大）影响和可靠测量。我们检查了影响最强和测量最可靠的情况，并使用合成数据集来说明影响大小、测量可靠性和统计功效之间的关系。然后，我们为更可靠的婴儿研究提出了六种具体解决方案：（a）定期估计和报告婴儿任务的效果大小和测量可靠性，（b）选择最佳测量工具，（c）开发更好的婴儿范式，(d) 为每个婴儿收集更多数据点，(e) 从分析中排除不可靠的数据，以及 (f) 进行更复杂的数据分析。在婴儿研究中更深入地考虑测量将提高我们研究婴儿发育的能力。