Correcting bias in extreme groups design using a missing data approach.

IF 7.6 1区心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY

Psychological methods Pub Date : 2024-12-01 Epub Date: 2022-07-18 DOI:10.1037/met0000508

Lihan Chen, Rachel T Fouladi

引用次数: 0

Abstract

Extreme groups design (EGD) refers to the use of a screening variable to inform further data collection, such that only participants with the lowest and highest scores are recruited in subsequent stages of the study. It is an effective way to improve the power of a study under a limited budget, but produces biased standardized estimates. We demonstrate that the bias in EGD results from its inherent missing at random mechanism, which can be corrected using modern missing data techniques such as full information maximum likelihood (FIML). Further, we provide a tutorial on computing correlations in EGD data with FIML using R. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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使用缺失数据方法纠正极端群体设计中的偏差。

极端组设计（EGD）是指使用筛选变量为进一步的数据收集提供信息，以便在研究的后续阶段只招募得分最低和最高的参与者。这是在预算有限的情况下提高研究能力的有效方法，但会产生有偏差的标准化估计。我们证明了EGD中的偏差是由于其固有的随机机制缺失造成的，这可以使用现代缺失数据技术如全信息最大似然（FIML）来纠正。此外，我们还提供了一个使用R. （PsycInfo Database Record (c) 2024 APA，版权所有）计算EGD数据与FIML相关性的教程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-

CiteScore

13.10

自引率

7.10%

发文量

159

期刊介绍： Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.