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An application of mixture distributions in modelization of length of hospital stay
Author(s) -
Atienza N.,
GarcíaHeras J.,
MuñozPichardo J. M.,
Villa R.
Publication year - 2007
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3029
Subject(s) - identifiability , mixture model , log normal distribution , estimator , weibull distribution , statistics , skewness , mathematics , variable (mathematics) , gamma distribution , econometrics , computer science , mathematical analysis
Length of hospital stay (LOS) is an important indicator of the hospital activity and management of health care. The skewness exhibited by this variable poses problems in statistical modeling. The aim of this work is to model the variable LOS within diagnosis‐related groups (DRG) through finite mixtures of distributions. A mixture of the union of Gamma, Weibull and Lognormal families is used in the model, instead of a mixture of a unique distribution family. Some theoretical questions regarding the model, such as the identifiability and study of asymptotic properties of ML estimators, are analyzed. The EM algorithm is proposed for performing these estimators. Finally, this new proposed model is illustrated by using data from different DRGs. Copyright © 2007 John Wiley & Sons, Ltd.