Loss to follow-up in cohort studies: How much is too much?

European Journal of Epidemiology

Volumn 19, Issue 8, 2004, Pages 751-760

  Kristman, Vicki ^a,c   Manno, Michael ^b,c   Côté, Pierre ^a,c  

^a INSTITUTE FOR WORK AND HEALTH   (Canada)

^b MOUNT SINAI HOSPITAL   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

Author keywords

Bias (epidemiology); Cohort studies; Computer simulation; Epidemiologic methods; Follow up studies; Logistic models

Indexed keywords

ARTICLE; COHORT ANALYSIS; CORRELATION ANALYSIS; DATA ANALYSIS; FOLLOW UP; LOGISTIC REGRESSION ANALYSIS; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL; CANADA; CONFIDENCE INTERVAL; EPIDEMIOLOGY; HUMAN; RISK; SENSITIVITY AND SPECIFICITY;

BIAS (EPIDEMIOLOGY); CANADA; COHORT STUDIES; CONFIDENCE INTERVALS; CONFOUNDING FACTORS (EPIDEMIOLOGY); EPIDEMIOLOGIC METHODS; FOLLOW-UP STUDIES; HUMANS; ODDS RATIO; SENSITIVITY AND SPECIFICITY;

EID: 16544389368     PISSN: 03932990     EISSN: 15737284     Source Type: Journal    
DOI: 10.1023/B:EJEP.0000036568.02655.f8     Document Type: Article

References (23)

1. Kleinbaum DG, Morgenstern H, Kupper LL. Selection bias in epidemiologic studies. Am J Epidemiol 1981; 113: 452-463.
2. Greenland S. Response and follow-up bias in cohort studies. Am J Epidemiol 1977; 106: 184-187.
3. Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Meth 2002; 7: 147-177.
4. Butler CW, Snyder M, Wood DE, Curtis JR, Albert RK, Benditt JO. Underestimation of mortality following lung volume reduction surgery resulting from incomplete follow-up. Chest 2001; 119: 1056-1060.
5. Rothman KJ, Greenland S. Modern Epidemiology. Philadelphia, PA: Lippincott-Raven, 1998.
6. Hollen PJ, Gralla RJ, Cox C, Eberly SW, Kris MG. A dilemma in analysis: issues in the serial measurement of quality of life in patients with advanced lung cancer. Lung Cancer 1997; 18: 119-136.
7. Deeg DJH. Attrition in longitudinal population studies: does it affect the generalizability of the findings? An introduction to the series. J Clin Epidemiol 2002; 55: 213-215.
8. Lohr SL. Nonresponse. In: Lohr SL (ed.), Sampling: design and analysis. Pacific Grove: Duxbury Press, 1999: 255-287.
9. Altman DG. Statistics in medical journals: some recent trends. Stat Med 2000; 19: 3275-3289.
10. Babbie ER. Survey research methods. Belmont, CA: Wadsworth, 1973.
11. Little RJA, Rubin DB. Statistical analysis with missing data. New York: John Wiley & Sons, 1987.
12. Twisk J, de Vente W. Attrition in longitudinal studies: how to deal with missing data. J Clin Epidemiol 2002; 55: 329-337.
13. Siddiqui O, Flay BR, Hu FB. Factors affecting attrition in a longitudinal smoking prevention study. Prev Med 1996; 25: 554-560.
14. Collins LM, Schafer JL, Kam C. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychol Meth 2001; 6: 330-351.
15. McLean RR, Hannan MT, Epstein BE, Bouxsein ML, Cupples LA, Murabito J, et al. Elderly cohort study subjects unable to return for follow-up have lower bone mass than those who can return. Am J Epidemiol 2000; 151: 689-692.
16. Bisgard KM, Folsom AR, Hong CP, Sellers TA. Mortality and cancer rates in nonrespondents to a prospective study of older women: 5-year follow-up. Am J Epidemiol 1994; 139: 990-1000.
17. Diggle PJ. Testing for random dropouts in repeated measurement data. Biometrics 1989; 45: 1255-1258.
18. Elashoff JD, Elashoff RM. Two-samples problems for a dichotomous variable with missing data. Appl Stats 1974; 23: 26-34.
19. Maldonado G, Greenland S. The importance of critically interpreting simulation studies. Epidemiology 1997; 8: 453-456.
20. Kristman V, Manno M, Côté P. The potential impact of attrition bias in cohort studies: A simulation study. Working Paper No. 180. Toronto: Institute for Work & Health, 2002.
21. Crawford SL, Tennstedt SL, McKinlay JB. A comparison of analytic methods for non-random missingness of outcome data. J Clin Epidemiol 1995; 48: 209-219.
22. Bootsma-van der Wiel A, van Exel E, de Craen AJM, Gussekloo J, Lagaay AM, Knook DL, et al. A high response is not essential to prevent selection bias: results from the Leiden 85-plus study. J Clin Epidemiol 2002; 55: 1119-1125.
23. Kempen GIJM, van Sonderen E. Psychological attributes and changes in disability among low-functioning older persons: does attrition affect the outcomes? J Clin Epidemiol 2002; 55: 224-229.