文章基本信息

标题：Configural analysis of oscillating progression
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作者：Alexander von Eye ; Wolfgang Wiedermann ; Stefan von Weber 等
期刊名称：Journal for Person-Oriented Research
印刷版ISSN：2002-0244
电子版ISSN：2003-0177
出版年度：2021
卷号：7
期号：1
DOI：10.17505/jpor.2021.23448
语种：English
出版社：Lund University Library
摘要：Oscillating series of scores can be approximated with locally optimized smoothing functions. In this article, we describe how such series can be approximated with locally estimated (loess) smoothing, and how Configural Frequency Analysis (CFA) can be used to evaluate and interpret results. Loess functions are often hard to describe because they cannot be represented by just one function that has interpretable parameters. In this article, we suggest that specification of the CFA base model be based on the width of the window that is used for local curve optimization, the weight given to data points in the neighborhood of the approximated one, and by the function that is used to locally approximate observed data. CFA types indicate that more cases were found than expected from the local optimization model. CFA antitypes indicate that fewer cases were found. In a real-world data example, the development of Covid-19 diagnoses in France is analyzed for the beginning period of the pandemic.