We regard the simple linear calibration problem where only the response y of the regression line y = 0 + 1 t is observed with errors. The experimental conditions t are observed without error. For the errors of the observations y we assume that there may be some gross errors providing outlying observations. This situation can be modeled by a conditionally contaminated regression model. In this m...

Title of dissertation: SAMPLING WEIGHT CALIBRATION WITH ESTIMATED CONTROL TOTALS Jill A. Dever, Doctor of Philosophy, 2008 Dissertation directed by: Professor Richard Valliant Joint Program in Survey Methodology Sample weight calibration, also referred to as calibration estimation, is a widely applied technique in the analysis of survey data. This method borrows strength from a set of auxiliary...

The estimation of a finite population distribution function is considered when there are missing data. Calibration adjustment used for dealing with nonresponse at the stage. Several procedures proposed and compared. A numerical study carried out to evaluate performances estimators. Computational problems implementation calibration estimators also considered.

A recently proposed Bayesian modeling framework for classification facilitates both the analysis and optimization of error estimation performance. The Bayesian error estimator is then defined to have optimal mean-square error performance, but in many situations closed-form representations are unavailable and approximations may not be feasible. To address this, we present a method to optimally c...

A unified framework to deal with the effective use of complete auxiliary information from survey data at the estimation stage has been attempted. The proposed method involves modeling the relationship between the variable of interest and the auxiliary variables, and then incorporating the auxiliary information into design-consistent estimators of finite population means, totals, distribution fu...

Remote sensing provides timely, economic, and objective data over a large area and has become the main data source for land cover/use area estimation. However, the classification results cannot be directly used to calculate the area of a given land cover/use type because of classification errors. The main purpose of this study is to explore the performance and stability of several model-assiste...

Summary In randomized experiments, adjusting for observed features when estimating treatment effects has been proposed as a way to improve asymptotic efficiency. However, among parametric methods, only linear regression proven form an estimate of the average effect that is asymptotically no less efficient than treated-minus-control difference in means regardless true data generating process. Ra...

In this paper, we first discuss the origin, developments and various thoughts by several researchers on the generalized linear regression estimator (GREG) due to Deville and Särndal [Deville, J.C., Särndal, C.E., 1992. Calibration estimators in survey sampling. J. Amer. Statist. Assoc. 87, 376–382]. Then, the problem of estimation of the general parameter of interest considered by Rao [Rao, J.N...

The problem of estimating the population mean using calibration estimators when some observations on the study and auxiliary characteristics are missing from the sample, is considered. Some new classes of estimators are proposed for any sampling design. These new classes employ to all observation (incomplete cases too) in the estimation without using any imputation techniques. On the basis of p...