A note on median regression for complex surveys. (29th October 2021)

• Record Type: Journal Article
• Authors: Fraser, Raphael A; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M
• Is Part Of: Biostatistics. Volume 23:Number 4(2022)
• Page Start: 1074
• Page End: 1082
• Publication Date: 2021-10-29
• Subjects: Asymptotic normality -- Bootstrap -- Complex survey -- Median regression -- Quantile regression -- Resampling methods -- Variance estimation; Medical statistics -- Periodicals; Biometry -- Periodicals; Health risk assessment -- Periodicals; Medicine -- Research -- Statistical methods -- Periodicals; 610.727
• DOI: 10.1093/biostatistics/kxab035
• Languages: English
• ISSNs: 1465-4644

Abstract

Summary: There is a great need for statistical methods for analyzing skewed responses in complex sample surveys. Quantile regression is a logical option in addressing this problem but is often accompanied by incorrect variance estimation. We show how the variance can be estimated correctly by including the survey design in the variance estimation process. In a simulation study, we illustrate that the variance of the median regression estimator has a very small relative bias with appropriate coverage probability. The motivation for our work stems from the National Health and Nutrition Examination Survey where we demonstrate the impact of our results on iodine deficiency in females compared with males adjusting for other covariates.