ERIC Number: EJ895493
Record Type: Journal
Publication Date: 2010-Sep
Abstractor: As Provided
Reference Count: 17
Modeling Noisy Data with Differential Equations Using Observed and Expected Matrices
Deboeck, Pascal R.; Boker, Steven M.
Psychometrika, v75 n3 p420-437 Sep 2010
Complex intraindividual variability observed in psychology may be well described using differential equations. It is difficult, however, to apply differential equation models in psychological contexts, as time series are frequently short, poorly sampled, and have large proportions of measurement and dynamic error. Furthermore, current methods for differential equation modeling usually consider data that are atypical of many psychological applications. Using embedded and observed data matrices, a statistical approach to differential equation modeling is presented. This approach appears robust to many characteristics common to psychological time series.
Descriptors: Psychometrics, Models, Statistical Analysis, Measurement, Measurement Techniques, Data, Equations (Mathematics), Calculus
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Authoring Institution: N/A