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A flexible parametric selection model for non‐normal data with application to health care usage
Author(s) -
Prieger James E.
Publication year - 2002
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.638
Subject(s) - weibull distribution , parametric statistics , selection (genetic algorithm) , model selection , parametric model , computer science , duration (music) , logistic regression , econometrics , sample (material) , statistics , operations research , machine learning , mathematics , art , chemistry , literature , chromatography
I examine the effects of insurance status and managed care on hospitalization spells, and develop a new approach for sample selection problems in parametric duration models. MLE of the Flexible Parametric Selection (FPS) model does not require numerical integration or simulation techniques. I discuss application to the exponential, Weibull, log‐logistic and gamma duration models. Applying the model to the hospitalization data indicates that the FPS model may be preferred even in cases in which other parametric approaches are available. Copyright © 2002 John Wiley & Sons, Ltd.