Parametric modelling of cost data: some simulation evidence

Briggs, A.H. , Nixon, R., Dixon, S. and Thompson, S. (2005) Parametric modelling of cost data: some simulation evidence. Health Economics, 14(4), pp. 421-428. (doi: 10.1002/hec.941)



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Recently, commentators have suggested that the distributional form of cost data should be explicitly modelled to gain efficiency in estimating the population mean. We perform a series of simulation experiments to evaluate the usual sample mean and the mean estimator of a lognormal distribution, in the context of both theoretical distributions and three large empirical datasets. The sample mean is always unbiased, but is somewhat less efficient when the population distribution is truly lognormal. However the lognormal estimator can perform appallingly when the true distribution is not lognormal. In practical situations, where the true distribution is unknown, the sample mean generally remains the estimator of choice, especially when limited sample size prohibits detailed modelling of the cost data distribution.

Item Type:Articles
Keywords:Cost analysis, simulation, lognormal.
Glasgow Author(s) Enlighten ID:Briggs, Professor Andrew
Authors: Briggs, A.H., Nixon, R., Dixon, S., and Thompson, S.
Subjects:R Medicine > RA Public aspects of medicine
R Medicine > R Medicine (General)
H Social Sciences > HG Finance
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
College of Medical Veterinary and Life Sciences
Journal Name:Health Economics
Copyright Holders:Copyright © 2005 Wiley
First Published:First published in Health Economics 14(4):421-428
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher.

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