Configural analysis of oscillating progression
| Autor: | Wolfgang Wiedermann, Stefan von Weber, Alexander von Eye |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Coronavirus disease 2019 (COVID-19)
Series (mathematics) Configural Frequency Analysis base model loess smoothing time series local optimization Covid-19 local optimization Articles Function (mathematics) Base (topology) loess smoothing BF1-990 base model Data point Configural Frequency Analysis Psychology Applied mathematics Development (differential geometry) Psychology (miscellaneous) time series Covid-19 Applied Psychology Smoothing Configural frequency analysis Mathematics |
| Zdroj: | Journal for Person-Oriented Research Journal for Person-Oriented Research, Vol 7, Iss 1 (2021) |
| ISSN: | 2003-0177 2002-0244 |
| DOI: | 10.17505/jpor.2021.23448 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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