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A flexible parametric selection model for non‐normal data with application to health care usage
81
Citations
38
References
2002
Year
Health Insurance DesignHospitalization SpellsInsurance RegulationsPublic HealthStatisticsHealth Services ResearchMedical StatisticHealth InformaticsHealth PolicyMedicineHealth Care AnalyticsHealth InsuranceNon‐normal DataOutcomes ResearchMedical Decision AnalysisMarginal Structural ModelsHealth Care DeliveryHealth EconomicsHealth DataLong-term Care InsuranceHealth Care ReimbursementHealth Care UsageTime-varying ConfoundingParametric Duration ModelsFlexible Parametric Selection
Abstract 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.
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