基于概率和测量的假设与充分约束的验证性因素分析研究——以认知心理学为例

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2011-01-01 DOI:10.1027/1614-2241/A000033
K. Schweizer
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引用次数: 2

摘要

对重复测量数据的验证性因子分析的概率和测量相关假设进行了研究。这些假设包含了关于与设计水平或测量项目相关的真实成分之间关系的精确假设。与测量相关的假设集中在假设的过程上,例如,转换和记忆过程,并代表了处理中依赖于治疗的差异。相比之下,基于概率的假设提供了机会,将概率视为总结各种影响影响的结果预测。用不精确的线索来预测表现就是一个例子。在本文的实证部分,基于概率和测量相关的假设应用于工作记忆数据。根据两种假设的潜在变量有助于良好的模型拟合。对于包含潜在变量的模型,达到了最佳的模型拟合。
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Probability-Based and Measurement- Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis An Example From Cognitive Psychology
Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented seri...
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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