通过增加使用均的便利样本来提高发展研究的普遍性:蒙特卡洛模拟
Justin Jager1, Yan Xia2, Diane L Putnick3
1T. Denny Sanford School of Social and Family Dynamics, Arizona State University.
Developmental psychology
|January 9, 2025
概括
在发育科学研究中使用均的便利样本 (CSs),特别是跨多个社会人口统计因素均的样本,可以显著减少采样偏差,并与异质的CSs相比提高概括性.
科学领域:
- 发展科学 发展科学
- 心理学 心理学 心理学
- 社会学 社会学 社会学
背景情况:
- 发展科学通常依赖于方便样本 (CSs),导致概括性问题并阻碍可复制性.
- 概率样本提供了更高的概括性,但其可行性是有限的.
- 现有的CS可以提供更明确的概括性,如果它们在关键的社会人口统计因素上是同质的.
研究的目的:
- 论证和正式测试为什么同质的CS提供了比异质的CS更清晰的概括性.
- 调查样本同质性对发育研究中的采样偏差的影响.
- 提议更多地使用同质的CSs来提高研究的概括性和可复制性.
主要方法:
- 这项研究提出了一个理论论点,即通过同质的CSs来增强可通用性.
- 蒙特卡洛模拟被用来正式测试这一论点.
- 模拟集中在与种族和社会经济地位相关的抽样偏见,以及青少年学业成绩.
主要成果:
- 蒙特卡洛模拟表明,同质的CS产生的估计比异质的CS少得多.
- 跨多个社会人口统计因素的同质性进一步增强了估计偏差的减少.
- 敏感性分析证实,偏差减少适用于平均值和关联的估计,尽管对关联来说不那么明显.
结论:
- 越来越多地利用同质的CSs,特别是那些跨多个社会人口统计因素均的CSs,可以大大提高发展研究的通用性.
- 这种方法对研究可复制性和少数群体研究有积极的影响.
- 该研究建议采用采样最佳实践,以提高发现的有效性和适用性.
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