 Diagnostic Tests for the Necessity of Weight in Regression With Survey DataFeng Wang, HaiYing Wang and Jun Yan International Statistical Review, 2023, vol. 91, issue 1, 55-71 Abstract: To weight or not to weight in regression analyses with survey data has been debated in the literature. The problem is essentially a tradeoff between the bias and the variance of the regression coefficient estimator. An array of diagnostic tests for informative weights have been developed. Nonetheless, studies comparing the performance of the tests, especially for finite samples, are scarce, and the theoretical equivalence of some tests has not been investigated. Focusing on the linear regression setting, we review a collection of such tests and propose enhanced versions of some of them that require an auxiliary regression model for the weight. Further, the equivalence of two popular tests is established which has not been reported before. In contrast to existing reviews with no empirical comparison, we compare the sizes and powers of the tests in simulation studies. The reviewed tests are applied to a regression analysis of the family expenditure using the data from the China Family Panel Study. Date: 2023 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:istatr:v:91:y:2023:i:1:p:55-71 Ordering information: This journal article can be ordered from Access Statistics for this article International Statistical Review is currently edited by Eugene Seneta and Kees Zeelenberg More articles in International Statistical Review from International Statistical Institute Contact information at EDIRC. |
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