Cited by 404Statistical Methods and Bayesian InferenceHealth Systems, Economic Evaluations, Quality of LifeStatistical Methods in Clinical Trials

Multiple regression of cost data: use of generalised linear models

Barber, Julie, Thompson, Simon·2004·Journal of Health Services Research & Policy

Abstract

Objective: Choosing an appropriate method for regression analyses of cost data is problematic because it must focus on population means while taking into account the typically skewed distribution of the data. In this paper we illustrate the use of generalised linear models for regression analysis of cost data. Methods: We consider generalised linear models with either an identity link function (providing additive covariate effects) or log link function (providing multiplicative effects), and with gaussian (normal), overdispersed poisson, gamma, or inverse gaussian distributions. These are applied to estimate the treatment effects in two randomised trials adjusted for baseline covariates. Criteria for choosing an appropriate model are presented. Results: In both examples considered, the gaussian model fits poorly and other distributions are to be preferred. When there are variables of prognostic importance in the model, using different distributions can materially affect the estimates obtained; it may also be possible to discriminate between additive and multiplicative covariate effects. Conclusions: Generalised linear models are attractive for the regression of cost data because they provide parametric methods of analysis where a variety of non-normal distributions can be specified and the way covariates act can be altered. Unlike the use of data transformation in ordinary least-squares regression, generalised linear models make inferences about the mean cost directly.

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Crossref · 10.1258/1355819042250249

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Authors
Barber, J., & Thompson, S.
Affiliations
  • University College London (GB)
  • MRC Biostatistics Unit (GB)
Venue
Journal of Health Services Research & Policy
Published
2004-10-02
Volume
9
Issue
4
Pages
197-204
ISSN
  • 1355-8196 (ISSN-L)
  • 1758-1060
OpenAlex
W1996146145
Cited by
404
References
20
Citations by year
2026: 11 · 2025: 11 · 2024: 17 · 2023: 18 · 2022: 27 · 2021: 29 · 2020: 32 · 2019: 29 · 2018: 32 · 2017: 28 · 2016: 28 · 2015: 23 · 2014: 22 · 2013: 17 · 2012: 20
FWCI
7.09
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Health Services Research & Policy (publishedVersion)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords
cost data, generalized linear models, skewed distributions, gamma distribution, inverse Gaussian distribution, log link function, treatment effects, baseline covariate adjustment, model selection criteria
MeSH terms
Costs and Cost Analysis, United Kingdom, Health Services Research, Normal Distribution, Linear Models

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