Free access to Tests for Regression Models Fitted to Survey Data

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  • Author: Statistics Views, Thomas Lumley and Alastair Scott
  • Date: 07 April 2014

Each week, we select an article hot off the press and provide free access for a limited period. This week's is from Australian & New Zealand Journal of Statistics, exclusively available from the Early View section, where articles are published prior to publication within a journal issue.

To read the article in full, please click on the link below.

Tests for Regression Models Fitted to Survey Data
Thomas Lumley and Alastair Scott

Australian & New Zealand Journal of Statistics, Early View
DOI: 10.1111/anzs.12065

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Data from complex surveys are being used increasingly to build the same sort of explanatory and predictive models as those used in the rest of statistics. Unfortunately the assumptions underlying standard statistical methods are not even approximately valid for most survey data. The problem of parameter estimation has been largely solved, at least for routine data analysis, through the use of weighted estimating equations, and software for most standard analytical procedures is now available in the major statistical packages. One notable omission from standard software is an analogue of the likelihood ratio test. An exception is the Rao–Scott test for loglinear models in contingency tables. In this paper, the authors show how the Rao–Scott test can be extended to handle arbitrary regression models. The authors illustrate the process of fitting a model to survey data with an example from NHANES.

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