使用模拟退火法研究 SEM 对外部模型不规范的敏感性。

IF 2.1 3区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Educational and Psychological Measurement Pub Date : 2023-02-01 Epub Date: 2022-01-31 DOI:10.1177/00131644211073121
Charles L Fisk, Jeffrey R Harring, Zuchao Shen, Walter Leite, King Yiu Suen, Katerina M Marcoulides
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引用次数: 0

摘要

敏感性分析包括一系列广泛的后分析技术,其特点是测量对模型的某些输出变量有影响的任何因素的潜在影响。本研究的重点是模拟退火算法在结构方程建模(SEM)中自动识别路径配置和遗漏混杂因素参数值的实用性。以过去发表的一项研究为基础,用一个实证例子说明了遗漏变量与模型变量之间必须有多大的关联才能改变分析结论。详细概述了算法,并讨论了敏感性分析的结果。
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Using Simulated Annealing to Investigate Sensitivity of SEM to External Model Misspecification.

Sensitivity analyses encompass a broad set of post-analytic techniques that are characterized as measuring the potential impact of any factor that has an effect on some output variables of a model. This research focuses on the utility of the simulated annealing algorithm to automatically identify path configurations and parameter values of omitted confounders in structural equation modeling (SEM). An empirical example based on a past published study is used to illustrate how strongly related an omitted variable must be to model variables for the conclusions of an analysis to change. The algorithm is outlined in detail and the results stemming from the sensitivity analysis are discussed.

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来源期刊
Educational and Psychological Measurement
Educational and Psychological Measurement 医学-数学跨学科应用
CiteScore
5.50
自引率
7.40%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Educational and Psychological Measurement (EPM) publishes referred scholarly work from all academic disciplines interested in the study of measurement theory, problems, and issues. Theoretical articles address new developments and techniques, and applied articles deal with innovation applications.
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