Adjusting for non-response in population-based case-control studies

International Statistical Review

Volumn 79, Issue 2, 2011, Pages 145-159

  Jiang, Yannan ^a   Scott, Alastair J ^a   Wild, Christopher J ^a  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

Conditional maximum likelihood; Non response; Response selective sampling; Semi parametric methods; Stratified case control studies; Weighted estimation

Indexed keywords

EID: 79961010560     PISSN: 03067734     EISSN: 17515823     Source Type: Journal    
DOI: 10.1111/j.1751-5823.2011.00132.x     Document Type: Article

References (47)

1. Anderson, J.A. (1972). Separate sample logistic discrimination. Biometrika, 59, 19-35.
2. Arbogast, P.G., Lin, D.Y., Siscovick, D.S. & Schwartz, S.M. (2002). Estimating incidence rates from population-based case-control studies in the presence of nonrespondents. Biom. J., 44, 227-239.
3. Binder, D.A. (1983). On the variances of asymptotically normal estimators from complex surveys. Int. Statist. Rev., 51, 279-292.
4. Breslow, N.E. (1996). Statistics in epidemiology: the case-control study. J. Amer. Statist. Assoc., 91, 14-28.
5. Breslow, N.E. (2005). Case-control studies. In Handbook of Epidemiology, Eds. W. Aherns & I. Pigeot, pp. 287-319. New York: Springer.
6. Breslow, N.E. & Cain, K.C. (1988). Logistic regression for two-stage case-control data. Biometrika, 75, 11-20.
7. Breslow, N.E. & Chatterjee, N. (1999). Design and analysis of two-phase studies with binary outcome applied to Wilms tumour prognosis. Appl. Statist., 48, 457-468.
8. Breslow, N.E. & Day, N.E. (1980). The Analysis of Case-Control Studies. Lyon: International Agency for Research on Cancer.
9. Carroll, R.J., Ruppert, D. & Stefanski, L.A. (1995). Measurement Error in Nonlinear Models. New York: Chapman and Hall.
10. Cordell, H.J. (2006). Estimation and testing in case-control studies: comparison of weighted regression and multiple imputation procedures. Genetic Epidemiol., 30, 259-275.
11. Elliott, M.R. & Little, R.J.A. (2000). Model-based alternatives to trimming survey weights. J. Official Statist., 16, 191-209.
12. Elliot, M.R., Little, R.J.A. & Lewitzky, S. (2000). Subsampling callbacks to improve survey efficiency. J. Amer. Statist. Assoc., 95, 730-738.
13. Galea, S. & Tracy, M. (2007). Participation rates in epidemiologic studies. Ann. Epidemiol., 17, 643-653.
14. Geneletti, S., Richardson, S. & Best, N. (2009). Adjusting for selection bias in retrospective case-control studies. Biostatistics, 10, 17-31.
15. Gebregziabher, M. & Langholz, B. (2010). A semiparametric missing-data induced intensity method for missing covariate data in individually matched case-control studies. Biometrics, 66, 845-854.
16. Hartge, P. (2006). Participation in population studies. Epidemiology, 17, 252-254.
17. Hausman, J.A. & Wise, D.A. (1982). Stratification on endogenous variables and estimation: the Gray income maintenance experiment. In Structural Analysis of Discrete Data: With Econometric Applications, Eds. C. Manski & D. McFadden, pp. 365-391. Cambridge, MA: MIT Press.
18. Henmi, M. & Eguchi, S. (2004). A paradox concerning nuisance parameters and projected estimating functions. Biometrika, 91, 929-941.
19. Jiang, Y. (2004). Semiparametric Maximum Likelihood for Multi-Phase Response-Selective Sampling and Missing Data Problems. Doctoral dissertation, the University of Auckland, New Zealand. Available at
20. Klebanoff, M.A. & Cole, S.R. (2008). Use of multiple imputation in the epidemiologic literature. Amer. J. Epidemiol., 168, 355-357.
21. Korn, E.L. & Graubard, B.I. (1999). Analysis of Health Surveys. New York: Wiley.
22. Lawless, J.F., Kalbfleish, J.D. & Wild, C.J. (1999). Semiparametric methods for response-selective and missing data problems in regression. J. R. Statist. Soc. B, 61, 413-438.
23. Lee, A.J., Scott, A.J. & Wild, C.J. (2010). Efficient estimation in multi-phase case-control studies. Biometrika, 97, 361-374.
24. Little, R.J.A. & Rubin, D.B. (2002). Statistical Analysis with Missing Data, 2nd ed. New York: John Wiley & Sons, Inc.
25. Lumley, T.S. (2010). Surveys: A Guide to Analysis Using R. New York: Wiley.
26. Manski, C.F. & McFadden, D. (1981). Structural Analysis of Discrete Data with Econometric Applications. Cambridge, MA: MIT Press.
27. Mantel, N. & Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. J. Nat. Cancer Inst., 22, 719-748.
28. McLeish, D.L. & Small, C.G. (1988). The Theory and Applications of Statistical Inference Functions. Springer Lecture Notes in Statistics #44, Berlin: Springer-Verlag.
29. Pfeffermann, D. (1993). The role of sampling weights when modeling survey data. Int. Statist. Rev., 61, 317-337.
30. Pfeffermann, D. & Sverchkov, M. (1999). Parametric and semi-parametric estimation of regression models fitted to survey data. Sankhya, 61, 166-186.
31. Prentice, R.L. & Pyke, R. (1979). Logistic disease incidence models and case-control studies. Biometrika, 66, 403-411.
32. Reeves, A.F., Rees, J.M., Schiff, M. & Hujoel, P. (2006). Total body weight and waist circumference associated with chronic periodontitis among adolescents in the US. Arch. Pediatr. Adolesc. Med., 160, 894-899.
33. Reilly, M. & Pepe, M.S. (1995). A mean score method for missing and auxiliary covariate data in regression models. Biometrika, 82, 299-314.
34. Richiardi, L., Boffetta, P. & Merletti, F. (2002). Analysis of non-response bias in a population based case-control study on lung cancer. J. Clin. Epidemiol., 55, 1033-1040.
35. Robins, J.M., Rotnitzky, A., Zhao, L.P. & Lipsitz, S. (1994). Estimation of regression coefficients when some regressors are not always observed. J. Amer. Statist. Assoc., 89, 846-866.
36. Rothman, K.J., Greenland, S. & Lash, T.L. (2008). Modern Epidemiology. Philadelphia: Wolters Kluwer Health.
37. Schill, W., Jockel, K.-H., Drescher, K. & Timm, J. (1993). Logistic analysis in case-control studies under validation sampling. Biometrika, 80, 339-352.
38. Schill, W. & Wild, P. (2006). Minimax designs for planning the second phase in a two-phase case-control study. Statist. Med., 25, 1646-1659.
39. Schwartz, S.M., Siscovick, D.S., Longstreth, W.T., Psaty, B.M., Beverly, R.K., Raghunathan, T.E., Lin, D.Y. & Koepsell, T.D. (1997). Low-dose oral contraceptive use and stroke in young women. Ann. Int. Med., 127, 596-602.
40. Scott, A.J. & Wild, C.J. (1986). Fitting logistic models under case-control or choice based sampling. J. R. Statist. Soc., B, 48, 170-182.
41. Scott, A.J. & Wild, C.J. (1997). Fitting regression models to case-control data by maximum likelihood. Biometrika, 84, 57-71.
42. Scott, A.J. & Wild, C.J. (2002). On the robustness of weighted methods for fitting model to case-control data by maximum likelihood. J. R. Statist. Soc., B, 64, 207-220.
43. Scott, A. & Wild, C. (2009). Population-based case-control studies. In Handbook of Statistics, Vol. 29B, Sample Surveys: Inference and Analysis, Eds. D. Pfeffermann & C. R. Rao, pp. 2, 431-453. Oxford: Elsevier.
44. Scott, A. & Wild, C. (2011). Fitting regression models with response-biased samples. Unpublished manuscript, last accessed: 10-02-2011.
45. Sorheim, I-C., Johannessen, A., Grydeland, T.B., Omenaas, E.R., Gulsvik, A. & Bakke, P.S. (2010). Case-control studies on risk factors for chronic obstructive pulmonary disease: how does the sampling for cases and controls affect the results Clin. Respit. J., 4, 89-96.
46. Stang, A. (2003). Non-response research: an underdeveloped field in epidemiology. Eur. J. Epidemiol., 18, 929-931.
47. White, J. E. (1982). A two stage design for the study of the relationship between a rare exposure and a rare disease. Amer. J. Epidemiol., 115, 119-128.