Estimation of regression coefficient from survey data based on test of significance

The ordinary least squares (OLS)estimator of regression coeffecient is implicitly based on I.I.D.assumption, which is rarely satisfied by survey data. Many approaches are proposed in the literature which can be classified in two broad categories as model based and design consistent.Du Mouchel and Duncan (1983) proposed a test statistic λwhich helps in testing the ignorability of sampling weights.In this article a preliminary test estimator based on λ is proposed. The model based properties of this estimator has been invetigated theoritically where as to study the design based properties simulation approach is adopted. It has been observed that the proposed estimator is a better cimpromise between model based and randomization based inferential frame work.