A Predictive Estimator of the Mean with Missing Data
Tóm tắt
One of the most difficult problems confronting investigators who analyze data from surveys is how treat missing data. Many statistical procedures can not be used immediately if any values are missing. This paper considers the problem of estimating the population mean using auxiliary information when some observations on the sample are missing and the population mean of the auxiliary variable is not available. We use tools of classical statistical estimation theory to find a suitable estimator. We study the model and design properties of the proposed estimator. We also report the results of a broad-based simulation study of the efficiency of the estimator, which reveals very promising results.
Tài liệu tham khảo
Allison P. (2000). Multiple imputation for missing data: a cuationary tale. Sociological Methods and Research 28(3): 301–309
Brick J.M., Kalton G. (1996). Handling missing data in survey research. Statistical methods in medical research 5: 215–238
Cassel, C. M., Särndal, C. E. and Wretman, J. H. (eds.). Foundations of Inference in Survey Sampling, New York: Wiley.
Díaz de Rada V. (2005). The effect of follow-up mailings on the response rate and response quality in mail surveys. Qualiy and Quantity 39: 1–18
Lavrakas P.J. (1993). Telephone Survey Methods. Sage, Newbury Park-California
Little R.J.A., Rubin D.B. (ed). (1987). Statistical Analysis with Missing Data. Wiley, New York
Mukhopadhyay, P. (eds.). Topics in Survey Sampling, New York: Springer-Verlag.
Rao C.R., Toutenburg H. (1995). Linear Models: Least Squares and Alternatives. Springer, New York
Rubin D.B. (1977). Formalizing subjective notions about the effect of nonrespondents in sample surveys. Journal of the American Statistical Association 72: 538–543
Rudas T. (2005). Mixture models of missing data. Quality and Quantity 39: 19–36
Rueda M., González S. (2004). Missing data and auxiliary information in surveys. Computational Statistic 19(4): 555–567
Sampath S., Chandra S.K. (1990). General class of estimators for the population total under unequal probability sampling schemes. Metron 48: 409–419
Schafer J.L. ed. (1997). Analysis of Imco mplete Multivariate Data. Chapman and Hall, London
Singh S. (ed). (2003). Advanced Sampling Theory with Applications. How Michael Selected Amy. Kluwer Academic Press, London
Singh S., Horn S., Tracy D.S. (2001). Hybrid of calibration and imputation: estimation of mean in survey sampling. Satisiica LXI(1): 27–41
Singh, S., Singh, H. P., Tailor, R. and Allen, J. (2002). General class of estimators for estimating ratio of two population means in the presence of random non-response. Working paper.
Srivastava S.K., Jhajj H.S. (1981). A class of estimators of the population mean in survey sampling using auxiliary information. Biometrika 68: 341–343
Toutenburg H., Srivastava V.K. (1988). Estimation of ratio of population means in survey sampling when some observations are missing. Metrika 48: 177–187
Tracy D.S., Osahan S.S. (1994). Random non-response on study variable versis on study as well as auxiliary variables. Statistica 54: 163–168
Valliant R., Dorfman A.H., Royall R.M. (ed). (2000). Finite Population Sampling and Inference. Wiley, New York
Willimack D.K. (1995). Effects of a prepaid nommonetary incentive on response rates and response quality in a face-to-face survey. Public Opinion Quarterly 59: 78–92