Optimal sample allocation for design-consistent regression in a cancer services survey when design variables are known for aggregates

Survey Methodology

Volumn 34, Issue 1, 2008, Pages 65-78

  Zaslavsky, Alan M ^a   Zheng, Hui ^b   Adams, John ^c  

^a HARVARD MEDICAL SCHOOL   (United States)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

^c RAND CORPORATION   (United States)

Author keywords

Descriptive population quantity; Measurement error; Neyman allocation; Regression models; Sample design; Surveys

Indexed keywords

EID: 84856490128     PISSN: 07140045     EISSN: 14920921     Source Type: Journal    
DOI: None     Document Type: Article

References (33)

1. Ayanian, J.Z., Chrischilles, E.A., Wallace, R.B., Fletcher, R.H., Fouad, M., Kiefe, C.I., Harrington, D.P., Weeks, J.C., Kahn, K.L., Malin, J.L., Lipscomb, J., Potosky, A.L., Provenzale, D.T., Sandler, R.S., Vanryn, M. and West, D.W. (2004). Understanding cancer treatment and outcomes: The Cancer Care Outcomes Research and Surveillance Consortium. Journal of Clinical Oncology, 2, 2992-2996.
2. Bellhouse, D.R. (1984). A review of optimal designs in survey sampling. The Canadian Journal of Statistics, 12, 53-65.
3. Binder, D.A. (1981). On the variances of asymptotically normal estimators from complex surveys. Survey Methodology, 7, 157-170.
4. Binder, D.A. (1983). On the variances of asymptotically normal estimators from complex surveys. International Statistical Review, 51, 279-292.
5. Botman, S.L., Moore, T.F., Moriarity, C.N. and Parsons, V.L. (2000). Design and Estimation for the National Health Interview Survey, 1995-2004. Vital and Health Statistics, 2(130). Washington, DC: National Center for Health Statistics.
6. Cassel, C.M., Särndal, C.-E. and Wretman, J.H. (1976). Some results on generalized difference estimation and generalized regression estimation for finite populations. Biometrika, 63, 615-620.
7. Chromy, J.R. (1987). Design optimization with multiple objectives. In Proceedings of the Section on Survey Research Methods, American Statistical Association. Alexandria, VA. 194-199.
8. Cochran, W.G. (1977). Sampling Techniques. New York: John Wiley & Sons, Inc.
9. Denton, N.A., and Massey, D.S. (1993). American Apartheid: Segregation and the Making of the Underclass. Cambridge, MA: Harvard University Press.
10. Dumouchel, W.H., and Duncan, G.J. (1983). Using sample survey weights in multiple regression analyses of stratified samples. Journal of the American Statistical Association, 78, 535-543.
11. Eaton, D.K., Kann, L., Kinchen, S., Ross, J., Hawkins, J., Harris, W.A., Lowry, R., Mcmanus, T., Chyen, D., Shanklin, S., Lim, C., Grunbaum, J.A. and Wechsler, H. (2006). Youth risk behavior surveillance - United States, 2005. Morbidity and Mortality Weekly Report, 55(SS-5), 1-108.
12. Fuller, W.A. (1975). Regression analysis for sample surveys. Sankhyā, C37, 117-132.
13. Fuller, W.A. (1984). Least squares and related analyses for complex survey designs. Survey Methodology, 10, 97-118.
14. Fuller, W.A. (2002). Regression estimation for survey samples. Survey Methodology, 28, 5-23.
15. Hansen, M.H., Madow, W.G. and Tepping, B.J. (1983). An evaluation of model-dependent and probability-sampling inferences in sample surveys. Journal of the American Statistical Association, 78, 776-793.
16. Isaki, C.T., and Fuller, W.A. (1982). Survey design under the regression superpopulation model. Journal of the American Statistical Association, 77, 89-97.
17. Kish, L. (1974). Optimal and proximal multipurpose allocation. Alexandria, VA. In Proceedings of the Social Statistics Section, American Statistical Association, 111-118.
18. Little, R.J.A. (1991). Inference with survey weights. Journal of Official Statistics, 7, 405-424.
19. McCullagh, P., and Nelder, J.A. (1989). Generalized Linear Models (Second Edition). London: Chapman & Hall Ltd.
20. Morel, J.G. (1989). Logistic regression under complex survey designs. Survey Methodology, 15, 203-223.
21. Morris, C., Newhouse, J.P. and Archibald, R. (1979). On the theory and practice of obtaining unbiased and efficient samples in social surveys and experiments. Research in Experimental Economics, 1, 199-220.
22. Nathan, G., and Holt, D. (1980). The effect of survey design on regression analysis. Journal of the Royal Statistical Society, Series B, Methodological, 42, 377-386.
23. Neyman, J. (1934). On the two different aspects of representative method: The method of stratified sampling and the method of purposive selection. Journal of the Royal Statistical Society, 97, 558-625.
24. Pfeffermann, D. (1993). The role of sampling weights when modeling survey data. International Statistical Review, 61, 317-337.
25. Royall, R.M. (1970). On finite population sampling theory under certain linear regression models. Biometrika, 57, 377-387.
26. Rubin, D.B. (1985). The use of propensity scores in applied Bayesian inference. In Bayesian Statistics 2, (Eds., J.M. Bernardo, M.H. DeGroot, D.V. Lindley and A.F.M. Smith). Amsterdam: Elsevier/North-Holland, 463-472.
27. Särndal, C.-E., Swensson, B. and Wretman, J. (1992). Model Assisted Survey Sampling. New York: Springer.
28. Sastry, N., Ghosh-Dastidar, B., Adams, J. and Pebley, A.R. (2005). The design of a multilevel survey of children, families, and communities: The Los Angeles Family and Neighborhood Survey. Social Science Research, 35, 1000-1024.
29. Thomsen, I., Tesfu, D. and Binder, D.A. (1986). Estimation of design effects and intraclass correlations when using outdated measures of size. International Statistical Review, 54, 343-349.
30. Valliant, R., Dorfman, A.H. and Royall, R.M. (2000). Finite Population Sampling and Inference: A Prediction Approach, New York: John Wiley & Sons, Inc.
31. Waksberg, J. (1973). The effect of stratification with differential sampling rates on attributes of subsets of the population. In ASA Proceedings of the Social Statistics Section, American Statistical Association. Alexandria, VA.
32. Waksberg, J. (1995). Distribution of poverty in census block groups (BGs) and implications for sample design. In ASA Proceedings of the Section on Survey Research Methods, American Statistical Association. Alexandria, VA, 497-502.
33. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817-838.