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Model-Based Prediction of the Population Proportion and Distribution Function Using a Logistic Regression
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 Title & Authors
Model-Based Prediction of the Population Proportion and Distribution Function Using a Logistic Regression
Park, Min-Gue;
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 Abstract
Estimation procedure of the finite population proportion and distribution function is considered. Based on a logistic regression model, an approximately model- optimal estimator is defined and conditions for the estimator to be design-consistent are given. Simulation study shows that the model-optimal design-consistent estimator defined under a logistic regression model performs well in estimating the finite population distribution function.
 Keywords
MLE;design consistency;distribution function estimation;model-based approach;
 Language
English
 Cited by
 References
1.
Chambers, R. L., Dorfman, A. H. and Hall, P. (1992). Properties of estimators of finite population distribution function, Biometrika, 79, 577-582 crossref(new window)

2.
Chambers, R. L. and Dunstan, R. (1986). Estimating distribution functions from survey data, Biometrika, 73, 597-604 crossref(new window)

3.
Fuller, W. A. (2008). Sampling Statistics, Iowa State University, Ames, IA.

4.
Gallant, A. R. (1987). Nonlinear Statistical Models, John Wiley & Sons, New York

5.
Harms, T. and Duchesne, P. (2006). On calibration estimation for quantiles, Survey methodology, 32, 37-52

6.
Horvitz, D. G. and Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe, Journal of the American Statistical Association, 47, 663-685 crossref(new window)

7.
Isaki, C. T. and Fuller, W. A. (1982). Survey design under the regression superpopulation model, Journal of the American Statistical Association, 77, 89-96 crossref(new window)

8.
Park, M. and Yang, M. (2008). Ridge regression estimation for survey samples, Communications in Statistics - Theory and Method, 37, 532-543 crossref(new window)

9.
Rao, J. N. K., Kovar, J. G. and Mantel, H. J. (1990). On estimating distribution functions and quantiles from survey data using auxiliary information, Biometrika, 77, 365-375 crossref(new window)

10.
Sarndal, C. E., Swensson, B. and Wretman, J. (1992). Model Assisted Survey Sampling, Springer-Verlag, New York

11.
Valliant, R., Dorfman, A. H. and Royall, R. M. (2000). Finite Population Sampling and Inference: A Prediction Approach, John Wiley & Sons, New York

12.
Wu, C. and Sitter, R. R. (2001). A model-calibration approach to using complete auxiliary information from survey data, Journal of the American Statistical Association, 96, 185-193 crossref(new window)