当前位置: X-MOL 学术Infant and Child Development › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
No data left behind
Infant and Child Development ( IF 1.776 ) Pub Date : 2022-05-24 , DOI: 10.1002/icd.2339
Ingmar Visser 1
Affiliation  

Infant research notoriously suffers from small samples, resulting in low power. Beyond increasing sample sizes, improving the reliability of our measurements can also increase power and help find more reliable effects. Byers-Heinlein, Bergmann and Savalei (2021) provide both an analysis of the problem of (low) reliability and a number of valuable recommendations. One of the recommendations is to ‘exclude unreliable data’. Although this may increase the effect size found in the remaining data, it can also unjustifiably bias the estimates when it is unknown what the cause of the unreliability is. In such cases, it is better to embrace the variability and use it to characterize the population: variability is also informative. Modern analytical techniques can be used to deal with variability and with missing data. No data should be left behind!

中文翻译:

没有留下任何数据

众所周知,婴儿研究的样本量小,导致功效低。除了增加样本量之外,提高我们测量的可靠性还可以增加功效并帮助找到更可靠的效果。Byers-Heinlein、Bergmann 和 Savalei (2021) 提供了对(低)可靠性问题的分析和一些有价值的建议。其中一项建议是“排除不可靠的数据”。尽管这可能会增加在剩余数据中发现的影响大小,但当不知道不可靠性的原因是什么时,它也可能会不合理地偏向估计值。在这种情况下,最好接受变异性并用它来表征人口:变异性也可以提供信息。现代分析技术可用于处理可变性和缺失数据。不应该留下任何数据!
更新日期:2022-05-24
down
wechat
bug