|
Abstract:
|
Most surveys are designed to provide statistics for a possibly (very) large number of characteristics of interest. Typically, the data collected are stored in a rectangular data file, each row corresponding to a sample unit and each column corresponding to a characteristic of interest. Made available on the data file is a weighting system. The idea is to construct a single weighting system applicable to all the characteristics of interest. The typical weighting process involves three major stages. At the first stage, each unit is assigned a base weight, defined as the inverse of its inclusion probability. The base weights are then modified to account for unit nonresponse. At the last stage, the weights adjusted for nonresponse are further modified to ensure consistency between survey estimates and known population totals. When needed, the weights undergo a last modification through weight trimming or weight smoothing methods in order to improve the efficiency of survey estimates. The goal of the course is to provide a detailed description of each stage. Participants should have a background in survey sampling and regression analysis. The course is intended to survey statisticians working in survey organizations, graduate students and users of survey data.
|
