Monday 11 February 2013

Analysing censored longitudinal data with non-ignorable missing values: depression in older age

an article by Milena Falcaro (London School of Hygiene and Tropical Medicine, London, UK), Neil Pendleton (University of Manchester, UK) and Andrew Pickles (King's College, London, UK) published in Journal of the Royal Statistical Society: Series A (Statistics in Society) Volume 176 Issue 2 (February 2013)

Summary

Missing values are common in cohort studies of the elderly.

As part of a study of cognition in older age, we implemented a model for the analysis of longitudinal depression data complicated by the presence of non-ignorable missing values, censored measurements and individually varying times of observation.

The repeated measures and non-response mechanisms are jointly modelled by assuming that they depend on a common underlying process.

The results of our analysis suggest that both depression and non-response increase with age and that women have systematically higher depression scores than men but do not have higher levels of study non-participation.


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