[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7465/jkdi.2014.25.1.263

Estimation using response probability when missing data happen on the second occasion

Park, Hyeonah (Department of Statistics, Seoul National University)
Na, Seongryong (Department of Information and Statistics, Yonsei University)

Publication Information

Journal of the Korean Data and Information Science Society / v.25, no.1, 2014 , pp. 263-269 More about this Journal

Abstract

When the loss of samples appears under repeated surveys, new samples can often replace missing values. Estimators using response probability can be considered under repeated surveys on two occasions where new samples are selected instead of missing data on the second occasion. We propose a new estimator that uses both respondents and new samples on the second occasion. It is considered for the simulation setting that missing values can happen at the second occasion and are replaced by new samples. We can see that the proposed estimator is more efficient than that using a weighting adjustment method for respondents at the second occasion.

Keywords

Repeated survey; response probability; two occasions;

Citations & Related Records

Times Cited By KSCI : 1 (Citation Analysis)

Reference
Cited By KSCI

1	Eltinge, J. L. and Yansaneh, I. S. (1997). Diagnostics for formation of nonresponse adjustment cells with an application to income nonresponse in the U.S. consumer expenditure survey. Survey Methodology, 23, 33-40.
2	Fuller, W. A. (1996). Introduction to statistical time series, Wiley, New York.
3	Isaki, C. T. and Fuller, W. A. (1982). Survey design under the regression superpopulation model. Journal of the American Statistical Association, 77, 89-96. DOI ScienceOn
4	Lipsitz, S. R., Ibrahim, J. G. and Zhao, L. P. (1999). A weighted estimating equation for missing covariate data with properties similar to maximum likelihood. Journal of the American Statistical Association, 94, 1147-1160. DOI ScienceOn
5	Little, R. J. A. (1986). Survey nonresponse adjustments. International Statistical Review, 54, 139-157. DOI ScienceOn
6	Lohr, S. L. (1999). Sampling: Design and analysis, Duxbury, California.
7	Park, H. and Park, W. (2013). Usage of auxiliary variable and neural network in doubly robust estimation. Journal of the Korean Data & Information Science Society, 24, 659-667. 과학기술학회마을 DOI ScienceOn
8	Robins, J. M., Rotnitzky, A. and Zhao, L. P. (1994). Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association, 89, 846-866. DOI ScienceOn
9	Rosenbaum, P. R. (1987). Model-based direct adjustment. Journal of the American Statistical Association, 82, 387-394. DOI ScienceOn