具有潜在变量的动态贝叶斯网络拟合的考虑:蒙特卡罗研究。

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Ray E Reichenberg, Roy Levy, Adam Clark
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引用次数: 1

摘要

动态贝叶斯网络;Reye, 2004)是一种很有前途的工具,可以在丰富的测量场景下模拟学生的熟练程度(Reichenberg, 2018)。这些场景通常呈现的评估条件比传统评估所看到的要复杂得多,需要能够整合这些复杂性的评估论证和心理测量模型。不幸的是,dbn仍未得到充分研究,其心理测量特性也相对未知。目前的工作旨在探索在各种现实心理测量条件下dbn的特性。为了使用最大似然估计评估dbn的参数恢复,进行了蒙特卡罗模拟研究。操纵因素包括样本量、测量质量、测试长度、测量次数。结果表明,度量质量对估计质量的影响最为显著,不同的性能类别产生更好的估计。从实际应用的角度来看,只要测量质量不差,每次测量至少有三个项目存在,只要样本低至N = 400,参数回收率似乎是足够的。仅由单一项目组成的测试需要特殊的测量质量,以便充分恢复模型参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study.

Dynamic Bayesian networks (DBNs; Reye, 2004) are a promising tool for modeling student proficiency under rich measurement scenarios (Reichenberg, 2018). These scenarios often present assessment conditions far more complex than what is seen with more traditional assessments and require assessment arguments and psychometric models capable of integrating those complexities. Unfortunately, DBNs remain understudied and their psychometric properties relatively unknown. The current work aimed at exploring the properties of DBNs under a variety of realistic psychometric conditions. A Monte Carlo simulation study was conducted in order to evaluate parameter recovery for DBNs using maximum likelihood estimation. Manipulated factors included sample size, measurement quality, test length, the number of measurement occasions. Results suggested that measurement quality has the most prominent impact on estimation quality with more distinct performance categories yielding better estimation. From a practical perspective, parameter recovery appeared to be sufficient with samples as low as N = 400 as long as measurement quality was not poor and at least three items were present at each measurement occasion. Tests consisting of only a single item required exceptional measurement quality in order to adequately recover model parameters.

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来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
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