Estimating a meaningful point of change: A comparison of exploratory techniques based on nonparametric regression

Klotsche, J. and Gloster, Andrew T.. (2012) Estimating a meaningful point of change: A comparison of exploratory techniques based on nonparametric regression. Journal of Education and Behavioral Statistics, 37 (5). pp. 579-600.

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Official URL: http://edoc.unibas.ch/48938/

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Longitudinal studies are increasingly common in psychological research. Characterized by repeated measurements, longitudinal designs aim to observe phenomena that change over time. One important question involves identification of the exact point in time when the observed phenomena begin to meaningfully change above and beyond baseline fluctuations. The authors introduce a nonparametric modeling framework to estimate the change-point of interest using derivatives of the underlying regression function for an outcome variable across time. The estimator of Huh and Carriere (HC) consistently performed acceptably when using a plug-in bandwidth in a Monte Carlo simulation study. It was shown that the estimator performed well with a minimum number of 15 design points. This procedure was applied to longitudinal data collected on performance anxiety. Results suggest that the HC estimator combined with plug-in bandwidth selection provides an efficient strategy for investigating a possible change-point at which an observed outcome variable starts changing across time.
Faculties and Departments:07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Klinische Psychologie und Neurowissenschaften > Klinische Psychologie und Epidemiologie (Lieb)
UniBasel Contributors:Gloster, Andrew
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:American Educational Research Association
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:22 Jan 2018 09:48
Deposited On:22 Jan 2018 09:48

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