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Testing the proportional odds assumption in multiply imputed ordinal longitudinal data

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Donneau, Anne-Françoise [Other] Mauer, Murielle E L [Autre] Lambert, Philippe [UCL] Lesaffre, Emmanuel M E H [KUL] Albert, Aurélie [ULg]

A popular choice when analyzing ordinal data is to consider the cumulative proportional odds model to relate the marginal probabilities of the ordinal outcome to a set of covariates. However, application of this model relies on the condition of identical cumulative odds ratios across the cut-offs of the ordinal outcome; the well-known proportional odds assumption. This paper focuses on the assessment of this assumption while accounting for repeated and missing data. In this respect, we develop a statistical method built on multiple imputation (MI) based on generalized estimating equations that allows to test the proportionality assumption under the missing at random setting. The performance of the proposed method is evaluated for two MI algorithms for incomplete longitudinal ordinal data. The impact of both MI methods is compared with respect to the type I error rate and the power for situations covering various numbers of categories of the ordinal outcome, sample sizes, rates of missingness, well-balanced and skewed data. The comparison of both MI methods with the complete-case analysis is also provided.We illustrate the use of the proposed methods on a quality of life data from a cancer clinical trial.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès restreint
Publication date 2015
Language Anglais
Journal information "Journal of Applied Statistics" - Vol. 42, no.10, p. 2257-2279 (2015)
Peer reviewed yes
Publisher Routledge (Abingdon)
issn 0266-4763
e-issn 1360-0532
Publication status Publié
Affiliation UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
Keywords categorical outcome ; clinical trials ; longitudinal analysis ; proportional odds assumption ; missing data ; multivariate normal imputation ; ordinal imputation model
Links
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Bibliographic reference Donneau, Anne-Françoise ; Mauer, Murielle E L ; Lambert, Philippe ; Lesaffre, Emmanuel M E H ; Albert, Aurélie. Testing the proportional odds assumption in multiply imputed ordinal longitudinal data. In: Journal of Applied Statistics, Vol. 42, no.10, p. 2257-2279 (2015)
Permanent URL http://hdl.handle.net/2078.1/168109