Literature DB >> 30639918

Does attrition affect estimates of association: A longitudinal study.

N Saiepour1, J M Najman2, R Ware1, P Baker1, A M Clavarino3, G M Williams1.   

Abstract

Survey research frequently involves missing cases attributable to refusals to participate, lack of success in accessing all potential respondents or loss to follow-up in longitudinal studies. There is concern that those not recruited or those lost are a select group whose absence from a study may bias the findings of the study. This study provides a test of the extent to which selective loss to follow-up in a longitudinal study may lead to biased findings. The Mater-University Study of Pregnancy collected baseline information for 7718 pregnant women. Follow-ups occurred five years, 14 years, 21 years and 27 years after the birth, for 6753 eligible women. Participants at baseline were partitioned according to follow-up status for each follow-up. We compare baseline (at recruitment) measures of association, with these same measures of association for those retained in the study (Group A) and those lost to follow-up (Group B) at each phase of data. Using univariate logistic regression we compared the strength of association between maternal mental health and various baseline socio-demographic factors for different rates of loss to follow-up. Estimates of association at baseline, and at each follow-up are similar irrespective of the rate of loss to follow-up and whether the comparison is with those retained in the study or those lost to follow-up. There were no statistically significant differences in 90.8% of baseline comparisons with Group A, and 96.9% of comparisons with Group B measures of association. We conclude that differential loss to follow-up rarely affects estimates of association. We suggest that loss to follow-up may produce misleading findings only in circumstances where loss to follow-up is combined with a number of other sources of bias.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Disadvantage; Loss to follow-up; Magnitude of bias; Mental disorder; Socio-economic

Mesh:

Year:  2018        PMID: 30639918     DOI: 10.1016/j.jpsychires.2018.12.022

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


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