Participant attrition from longitudinal research studies is a concern for social scientists because loss of certain subgroups of participants may result in subsequent data collection phases becoming increasingly biased. This article examines whether attrition has been given due consideration in selected reports of longitudinal research undertaken by social scientists. Results of a review of the literature found that less than one-quarter of the studies described how data were examined for patterns of attrition. On the other hand, those articles that described the treatment of attrition used solutions that were varied and often simple and effective. Recommendations for statistical and nonstatistical ways of dealing with sample attrition used by social scientists are provided.
Alderman, H., J. R. Behrman, H. P. Kohler, J. A. Maluccio, and S. C. Watkins. 2000. Attrition in longitudinal household survey data: Some tests for three developing-country samples. Unpublished manuscript, Washington, DC.
2.
Alexander, P.1993.The differential effects of abuse characteristics and attachmentin the prediction of long-term effects of sexual abuse. Journal of Interpersonal Violence8:346–362.
3.
Baker, D., K. North, and T. A. S. Team. 1999. Does employment improve the health of lone mothers?Social Science and Medicine49:121–131.
4.
Bebbington, P., T. Brugha, H. Meltzer, M. Farrell, C. Ceresa, R. Jenkins, and G. Lewis. 2000. Psychiatric disorder and dysfunction in the UK National Survey of Psychiatric Morbidity. Social Psychiatry and Psychiatric Epidemiology35:191–197.
5.
Bergman, M. M., and J. Scott. 2001. Young adolescents’ well-being and health-risk behaviours: Gender and socio-economic differences. Journal of Adolescence24(2): 183–197.
6.
Bor, W., K. Anstley, J. Najman, M. O’Callaghan, G. Williams, and M. Anderson. 1998. An Australian longitudinal study of factors leading to childhood aggression and subsequent delinquency. Report for the Australian Institute of Criminology. Brisbane, UK: Department of Anthropology and Sociology, University of Queensland.
7.
Bor, W., J. Najman, M. Anderson, J. Morrison, and G. Williams. 1993. Socioeconomic disadvantage and child morbidity: An Australian longitudinal study. Social Science and Medicine36(8): 1053–1061.
8.
Botwinick, J., and I. C. Siegler. 1980. Intellectual ability among the elderly: Simultaneous cross-sectional and longitudinal comparisons. Developmental Psychology16(1): 49–53.
9.
Buchanan, A., and E. Flouri. 2001. Recovery after age 7 from externalising behaviour problems: The role of risk and protective clusters. Children and Youth Services Review23(12): 899–914.
10.
Buchanan, A., E. Flouri, and J. T. Brinke. 2002. Emotional and behavioural problems in childhood and distress in adult life: Risk and protective factors. Australian and New Zealand Journal of Psychiatry36:521–527.
11.
Burkam, D., and V. Lee. 2000. Effects of monotone and nonmonotone attrition on parameter estimates in regression models with educational data. The Journal of Human Resources33(2): 555–572.
12.
Cheung, Y. B.2002.A confirmatory factor analysis of the 12-item General Health Questionnaire among older people. International Journal of Geriatric Psychiatry17(8): 739–744.
13.
Davey, A., M. Shanahan, and J. Schafer. 2001. Correcting for selective nonresponse in the national longitudinal survey of youth using multiple imputation. The Journal of Human Resources36(3): 500–519.
14.
Dworsky, A. L., and I. Piliavin. 2000. Homeless spell exits and returns: Substantive and methodological elaborations on recent studies. Social Service Review74(2): 193–213.
15.
Fitzgerald, J., P. Gottschalk, and R. Moffitt. 1998. An analysis of sample attrition in panel data: The Michigan Panel Study of Income Dynamics. The Journal of Human Resources33(2): 251–300.
16.
Flouri, E., and A. Buchanan. 2003. The role of father involvement in children’s later mental health. Journal of Adolescence26:63–78.
17.
Frank, D. J., S. Y. Wong, J. W. Meyer, and F. O. Ramirez. 2000. What counts as history: A cross-national and longitudinal study of university curricula. Comparative Education Review44(1): 29-29.
18.
Frank, G. C., P. R. Nader, M. M. Zive, S. L. Broyles, and J. J. Brennan. 2003. Retaining school children and families in community research: Lessons from the Study of Children’s Activity and Nutrition. Journal of School Health73(2): 51–58.
19.
Goldberg, P., A. Gueguen, A. Schmaus, J. P. Nakache, and M. Goldberg. 2001. Longitudinal study of associations between perceived health status and self reported diseases in the French Gazel cohort. Journal of Epidemiology & Community Health55(4): 233-233.
20.
Goodman, J. S., and T. C. Blum. 1996. Assessing the non-random sampling effects of subject attrition in longitudinal research. Journal of Management22(4): 627–653.
21.
Hausman, J. A., and D. A. Wise. 1979. Attrition bias in experimental and panel data: The Gary Income Maintenance Experiment. Econometrica47(2): 455–474.
22.
Hayslip, B., L. McCoy-Roberts, and R. Pavur. 1998. Selective attrition effects in bereavement research: A three-year longitudinal analysis. Omega38(1): 21–35.
23.
Heckman, J.1976. The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement5:475–492.
24.
Heckman, J.1979. Sample selection bias as a specification error. Econometrica47:153–161.
25.
Hirano, K., G. W. Imbens, G. Ridder, and D. B. Rubin. 2001. Combining panel data sets with attrition and refreshment samples. Econometrica69:1645–1659
26.
Levin, B., H. Katzen, B. Klein, and M. Llabre. 2000. Cognitive decline affects subject attrition in longitudinal research. Journal of Clinical and Experimental Neuropsychology22(5): 580–586.
27.
Lillard, L. A., and W. A. Constantijn-Panis. 1998. Panel attrition for the panel study of income dynamics: Household income, marital status. The Journal of Human Resources33(2): 437–448.
28.
Little, R. J. A.1995. Modeling the drop-out mechanism in repeated-measures studies. Journal of the American Statistical Association90(431): 112-112.
29.
Little, R. J. A., and D. B. Rubin. 2000. Causal effects in clinical and epidemiological studies via potential outcomes: Concepts and analytical approaches. Annual Review of Public Health21:121–145.
30.
MaCurdy, T., T. Mroz, and R. M. Gritz. 1998. An evaluation of the National Longitudinal Survey on Youth. The Journal of Human Resources33(2): 345–436.
31.
Miller, R., and D. Wright. 1995. Detecting and correcting attrition bias in longitudinal family research. Journal of Marriage and the Family57(4): 921–946.
32.
Nigg, J. T., J. P. Quamma, M. T. Greenberg, and C. A. Kusche. 1999. A two-year longitudinal study of neuropsychological and cognitive performance in relation to behavioral problems and competencies in elementary school children. Journal of Abnormal Child Psychology27(1): 51–57.
33.
Rubin, D. B.1976. Inference and missing data. Biometrika63(3): 581–592.
34.
Russell, S. T.2002. Childhood developmental risk for teen childbearing in Britain. Journal of Research on Adolescence12(3): 305–324.
35.
Sacker, A., I. Schoon, and M. Bartley. 2002. Social inequality in educational achievement and psychosocial adjustment throughout childhood: Magnitude and mechanisms. Social Science and Medicine55:863–880.
36.
Sanson, A., J. Nicholson, J. Ungerer, S. Zubrick, K. Wilson, J. Ainley, D. Berthelsen, M. Bittman, D. Broom, L. Harrison, B. Rodgers, M. Sawyer, S. Silburn, L. Strazdins, G. Vimpani, and M. Wake. 2002. Introducing the Longitudinal Study of Australian Children. LSAC discussion paper no. 1. Melbourne: Australian Institute of Family Studies.
37.
Siddiqui, O., B. Flay, and F. Hu. 1996. Factors affecting attrition in a longitudinal smoking prevention study. Preventative Medicine25:554–560.
38.
Simkin, L. S., L. Hirsch, A. Radosh, S. E. Middlestadt, J. Kaiser, and J. S. Santelli. 2000. Strategies to maximize retention of a sample of young adolescents in a longitudinal evaluation of Healthy & Alive!Journal of School Health70 (7): 286-286.
39.
Smith, R.1996. Capturing sensitive data from young people in a household setting. Journal of the Market Research Society38(2): 177–183.
40.
Stratford, R., J. Mulligan, B. Downie, and L. Voss. 1999. Threats to validity in the longitudinal study of psychological effects: the case of short stature. Child: Care, Health and Development25(6): 401–419.
41.
Sullivan, O.1997. The division of household work among “remarried” couples. Journal of Family Issues18(2): 205–223.
42.
Thomas, D., E. Frankenberg, and J. Smith. 2001. Lost but not forgotten: Attrition and follow up in the Indonesia Family Life Survey. The Journal of Human Resources36(3): 556–592.
43.
Twisk, J., and W. de Vente. 2002. Attrition in longitudinal studies: How to deal with missing data. Journal of Clinical Epidemiology55:329–337.
44.
Whiteman, D. C., M. P. Dunne, and P. C. Burnett. 1995. Psychological and social correlates of attrition in a longitudinal study of hazardous waste exposure. Archives of Environmental Health50(4): 281–287.
45.
Winefield, A. H., H. R. Winefield, and M. Tiggemann.1990. Sample attrition bias in a longitudinal study of young people. Australian Journal of Psychology42(1): 75–85.
46.
Yau, L. H. Y., and R. J. Little. 2001. Inference for the compiler-averagecausal effect from longitudinal data subject to noncompliance and missing data, with application to a job training assessment for the unemployed. Journal of the American Statistical Association96(456): 1232–1244.
47.
Zabel, J.1998. An analysis of attrition in the Panel Study of Income Dynamics and the Survey of Income and Program Participation with an application to a model of labor market behavior. The Journal of Human Resources33(2): 479–506.
48.
Zipp, J. F., and J. Toth. 2002. He said, she said, they said: The impact of spousal presence in survey research. Public Opinion Quarterly66(2): 177–208.
