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Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders

Research output: Contribution to journalArticle

  • Dieter Wolke
  • Andrea Waylen
  • Muthanna Samara
  • Colin Steer
  • Robert Goodman
  • Tamsin Ford
  • Koen Lamberts
Translated title of the contributionSelective drop-out in longitudinal studies and non-biased prediction of behaviour disorders
Original languageEnglish
Pages (from-to)249 - 256
Number of pages8
JournalBritish Journal of Psychiatry
Volume195
DOIs
DatePublished - Sep 2009

Abstract

Background Participant drop-out occurs in all longitudinal studies, and if systematic, may lead to selection biases and erroneous conclusions being drawn from a study. Aims We investigated whether drop out in the Avon Longitudinal Study of Parents And Children (ALSPAC) was systematic or random, and if systematic, whether it had an impact on the prediction of disruptive behaviour disorders. Method Teacher reports of disruptive behaviour among currently participating, previously participating and never participating children aged 8 years in the ALSPAC longitudinal study were collected. Data on family factors were obtained in pregnancy. Simulations were conducted to explain the impact of selective drop-out on the strength of prediction. Results Drop out from the ALSPAC cohort was systematic and children who dropped out were more likely to suffer from disruptive behaviour disorder. Systematic participant drop-out according to the family variables, however, did not alter the association between family factors obtained in pregnancy and disruptive behaviour disorder at 8 years of age. Conclusions Cohort studies are prone to selective drop-out and are likely to underestimate the prevalence of psychiatric disorder. This empirical study and the simulations confirm that the validity of regression models is only marginally affected despite range restrictions after selective drop-out.

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