Detection of Outliers Due to Participants’ Non-Adherence to Protocol in a Longitudinal Study of Cognitive Decline

Aline Dugravot, Severine Sabia, Martin J Shipley, Catherine Welch, Mika Kivimaki and Archana Singh-Manoux

PLOS ONE, 2015, vol. 10, issue 7, 1-13

Abstract: Background: Participants’ non adherence to protocol affects data quality. In longitudinal studies, this leads to outliers that can be present at the level of the population or the individual. The purpose of the present study is to elaborate a method for detection of outliers in a study of cognitive ageing. Methods: In the Whitehall II study, data on a cognitive test battery have been collected in 1997-99, 2002-04, 2007-09 and 2012-13. Outliers at the 2012-13 wave were identified using a 4-step procedure: (1) identify cognitive tests with potential non-adherence to protocol, (2) choose a prediction model between a simple model with socio-demographic covariates and one that also includes health behaviours and health measures, (3) define an outlier using a studentized residual, and (4) study the impact of exclusion of outliers by estimating the effect of age and diabetes on cognitive decline. Results: 5516 participants provided cognitive data in 2012-13. Comparisons of rates of annual decline over the first three and all four waves of data suggested outliers in three of the 5 tests. Mean residuals for the 2012-13 wave were larger for the basic compared to the more complex prediction model (all p

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0132110

DOI: 10.1371/journal.pone.0132110

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