Generalized shared-parameter models and missingness at random


Creemers, A; Hens, N; Aerts, M; Molenberghs, G; Verbeke, G; Kenward, MG; (2011) Generalized shared-parameter models and missingness at random. Statistical modelling, 11 (4). pp. 279-310. ISSN 1471-082X DOI: https://doi.org/10.1177/1471082x1001100401

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Abstract

When data are incomplete, models are often catalogued according to one of the three modelling frameworks to which they belong: selection models (SeM), pattern-mixture models (PMM) and shared-parameter models (SPM). The missing data mechanism is conventionally classified as missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR). Under MCAR, measurement and missingness mechanism are independent, but that is not the case for MAR. The definition of MAR is in SeM terms. Molenberghs et al. (1998) provided a characterization for PMM. Here, MAR is characterized in the SPM framework, using an extended SPM class. A subfamily, satisfying the MAR condition, is studied in detail. Particular implications for non-monotone missingness as well as for longitudinal data subject to dropout are studied. It is indicated how SPM can be constrained such that dropout at a given point in time can depend on current and past, but not on future measurements. Although, a natural requirement, it is less easily imposed in the PMM and SPM frameworks than in the SeM case. Some of the models proposed are illustrated using a clinical trial in toenail dermatophyte onychomycosis.

Item Type: Article
Keywords: available-case missing value restrictions, ignorability, missing at, random counterpart, missing completely at random, missing, non-future-dependent restrictions, non-future dependence, pattern-mixture model, selection model, pattern-mixture models, surrogate end-points, longitudinal data, incomplete data, clinical-trials, linear-model, cd4 counts, drop-out, survival, aids, llmann d, 1995, v51, p151, mpster ap, 1977, v39, p1, gruttola v, 1994, v50, p1003, ylor jmg, 1994, v89, p727
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Medical Statistics
Research Centre: Centre for Statistical Methodology
Web of Science ID: 293922900002
URI: http://researchonline.lshtm.ac.uk/id/eprint/141

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