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Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study

BMC public health, 2012-10, Vol.12 (1), p.918-918, Article 918 [Peer Reviewed Journal]

COPYRIGHT 2012 BioMed Central Ltd. ;2012 Gustavson et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ;info:eu-repo/semantics/openAccess ;Copyright ©2012 Gustavson et al.; licensee BioMed Central Ltd. 2012 Gustavson et al.; licensee BioMed Central Ltd. ;ISSN: 1471-2458 ;EISSN: 1471-2458 ;DOI: 10.1186/1471-2458-12-918 ;PMID: 23107281

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  • Title:
    Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study
  • Author: Gustavson, Kristin ; von Soest, Tilmann ; Karevold, Evalill ; Røysamb, Espen
  • Subjects: Adult ; Attrition ; Bias ; Child development ; Computer Simulation ; Confidence intervals ; Female ; Follow-Up Studies ; Health aspects ; Humans ; Longitudinal method ; Longitudinal Studies ; Measurement ; Medical research ; Mental disorders ; Mental health ; Methods ; Monte Carlo Method ; Mothers - statistics & numerical data ; Patient Dropouts - statistics & numerical data ; Public health ; Regression analysis ; Risk Factors ; Sample size ; Selection bias ; Simulation ; Studies ; Time Factors
  • Is Part Of: BMC public health, 2012-10, Vol.12 (1), p.918-918, Article 918
  • Description: Attrition is one of the major methodological problems in longitudinal studies. It can deteriorate generalizability of findings if participants who stay in a study differ from those who drop out. The aim of this study was to examine the degree to which attrition leads to biased estimates of means of variables and associations between them. Mothers of 18-month-old children were enrolled in a population-based study in 1993 (N=913) that aimed to examine development in children and their families in the general population. Fifteen years later, 56% of the sample had dropped out. The present study examined predictors of attrition as well as baseline associations between variables among those who stayed and those who dropped out of that study. A Monte Carlo simulation study was also performed. Those who had dropped out of the study over 15 years had lower educational level at baseline than those who stayed, but they did not differ regarding baseline psychological and relationship variables. Baseline correlations were the same among those who stayed and those who later dropped out. The simulation study showed that estimates of means became biased even at low attrition rates and only weak dependency between attrition and follow-up variables. Estimates of associations between variables became biased only when attrition was dependent on both baseline and follow-up variables. Attrition rate did not affect estimates of associations between variables. Long-term longitudinal studies are valuable for studying associations between risk/protective factors and health outcomes even considering substantial attrition rates.
  • Publisher: England: BioMed Central Ltd
  • Language: English
  • Identifier: ISSN: 1471-2458
    EISSN: 1471-2458
    DOI: 10.1186/1471-2458-12-918
    PMID: 23107281
  • Source: Open Access: DOAJ Directory of Open Access Journals
    Open Access: PubMed Central
    AUTh Library subscriptions: ProQuest Central
    GFMER Free Medical Journals
    MEDLINE
    NORA Norwegian Open Research Archives
    Springer Open Access Journals
    ROAD: Directory of Open Access Scholarly Resources
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