Approximate Tests of Independence and Goodness of Fit Based on Stratified Multistage Samples

Publisher Website
Google Scholar
Abstract
The impact on linear statistics of the sample design used in obtaining survey data is the subject of much of sampling literature. Recently, more attention has been paid to the design's impact on nonlinear statistics; the major factor inhibiting these investigations has been the problem of estimating at least the first two moments of such statistics. The present article examines the problem of estimating the variances of nonlinear statistics from complex samples, in the light of existing literature. The behavior of the chi-squared statistic computed from a complex sample to test hypotheses of goodness of fit or independence is studied. Alternative tests are developed and their properties studied in simulation experiments.

This publication has 0 references indexed in Scilit: