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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
Unit of Nutritional Epidemiology
Institute of Environmental Medicine, Karolinska Institutet
Stockholm, Sweden
Matteo Bottai
Division of Biostatistics
University of South Carolina
Columbia, SC
Unit of Biostatistics
Institute of Environmental Medicine, Karolinska Institutet
Stockholm, Sweden
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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