Empirical evaluation of statistical models for counts or rates
- 1 September 1991
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 10 (9) , 1405-1416
- https://doi.org/10.1002/sim.4780100908
Abstract
We consider methods for selecting the joint specification of the mean and variance functions in statistical models for rates or counts. Based on analyses of diagnosis‐specific hospital discharge rates in Michigan, we show that a Poisson model with an extra variance component for the systematic variation is superior to several other probability models with regard to specification of the error structure. Further, the deviance residual appears superior to the Pearson residual. The proper specification of such variation is crucial for many types of analyses, such as identification of outliers and regression analyses designed to explain the systematic component of the variation.Keywords
This publication has 15 references indexed in Scilit:
- Small Area Variations: A Critical Review of Propositions, Methods, and EvidenceMedical Care Review, 1990
- Variation in Hospital Admissions Among Small Areas: A Comparison of Maine and MichiganMedical Care, 1989
- Regression Methods for Poisson Process DataJournal of the American Statistical Association, 1987
- ARE HOSPITAL SERVICES RATIONED IN NEW HAVEN OR OVER-UTILISED IN BOSTON?The Lancet, 1987
- Testing Goodness of Fit for the Poisson Assumption When Observations are Not Identically DistributedJournal of the American Statistical Association, 1985
- Extra-Poisson Variation in Log-Linear ModelsJournal of the Royal Statistical Society Series C: Applied Statistics, 1984
- Multiplicative Models and Cohort AnalysisJournal of the American Statistical Association, 1983
- Small-Area Variations in the Use of Common Surgical Procedures: An International Comparison of New England, England, and NorwayNew England Journal of Medicine, 1982
- Small Area Variations in Health Care DeliveryScience, 1973