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Hunger, M. ; Döring, A. ; Holle, R.

Longitudinal beta regression models for analyzing health-related quality of life scores over time.

BMC Med. Res. Methodol. 12:144 (2012)
Verlagsversion Volltext DOI PMC
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ABSTRACT: BACKGROUND: Health-related quality of life (HRQL) has become an increasingly important outcome parameter in clinical trials and epidemiological research. HRQL scores are typically bounded at both ends of the scale and often highly skewed. Several regression techniques have been proposed to model such data in cross-sectional studies, however, methods applicable in longitudinal research are less well researched. This study examined the use of beta regression models for analyzing longitudinal HRQL data using two empirical examples with distributional features typically encountered in practice. METHODS: We used SF-6D utility data from a German older age cohort study and stroke-specific HRQL data from a randomized controlled trial. We described the conceptual differences between mixed and marginal beta regression models and compared both models to the commonly used linear mixed model in terms of overall fit and predictive accuracy. RESULTS: At any measurement time, the beta distribution fitted the SF-6D utility data and strokespecific HRQL data better than the normal distribution. The mixed beta model showed better likelihood-based fit statistics than the linear mixed model and respected the boundedness of the outcome variable. However, it tended to underestimate the true mean at the upper part of the distribution. Adjusted group means from marginal beta model and linear mixed model were nearly identical but differences could be observed with respect to standard errors. CONCLUSIONS: Understanding the conceptual differences between mixed and marginal beta regression models is important for their proper use in the analysis of longitudinal HRQL data. Beta regression fits the typical distribution of HRQL data better than linear mixed models, however, if focus is on estimating group mean scores rather than making individual predictions, the two methods might not differ substantially.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Health-related quality of life; Beta regression; Longitudinal study; Mixed model; Marginal model; MISSING DATA; OUTCOMES; VARIABLES; STROKE; REHABILITATION; APPROPRIATE; IMPACT; RATES; GEE
Sprache englisch
Veröffentlichungsjahr 2012
HGF-Berichtsjahr 2012
e-ISSN 1471-2288
Zeitschrift BMC Medical Research Methodology
Quellenangaben Band: 12, Heft: , Seiten: , Artikelnummer: 144 Supplement: ,
Verlag BioMed Central
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Health Economics and Health Care Management (IGM)
POF Topic(s) 30202 - Environmental Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-505300-002
PubMed ID 22984825
DOI 10.1186/1471-2288-12-144
WOS ID WOS:000312800900001
Scopus ID 84866182969
Erfassungsdatum 2012-12-03
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