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The Stata Journal
Volume 11 Number 3: pp. 327-344



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Logistic quantile regression in Stata

Nicola Orsini
Unit of Biostatistics
and
Unit of Nutritional Epidemiology
Institute of Environmental Medicine, Karolinska Institutet
Stockholm, Sweden
nicola.orsini@ki.se
Matteo Bottai
Division of Biostatistics
University of South Carolina
Columbia, SC
and
Unit of Biostatistics
Institute of Environmental Medicine, Karolinska Institutet
Stockholm, Sweden
matteo.bottai@ki.se
Abstract.  We present a set of Stata commands for the estimation, prediction, and graphical representation of logistic quantile regression described by Bottai, Cai, and McKeown (2010, Statistics in Medicine 29: 309–317). Logistic quantile regression models the quantiles of outcome variables that take on values within a bounded, known interval, such as proportions (or percentages) within 0 and 1, school grades between 0 and 100 points, and visual analog scales between 0 and 10 cm. We describe the syntax of the new commands and illustrate their use with data from a large cohort of Swedish men on lower urinary tract symptoms measured on the international prostate symptom score, a widely accepted score bounded between 0 and 35.
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