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Quantile regression in the study of developmental sciences.

Title: Quantile regression in the study of developmental sciences.
Name(s): Petscher, Yaacov, author
Logan, Jessica A R, author
Type of Resource: text
Genre: Text
Date Issued: 2014-05-01
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of the outcome's distribution. Using data from the High School and Beyond and U.S. Sustained Effects Study databases, quantile regression is demonstrated and contrasted with linear regression when considering models with: (a) one continuous predictor, (b) one dichotomous predictor, (c) a continuous and a dichotomous predictor, and (d) a longitudinal application. Results from each example exhibited the differential inferences which may be drawn using linear or quantile regression.
Identifier: FSU_pmch_24329596 (IID), 10.1111/cdev.12190 (DOI), PMC4166511 (PMCID), 24329596 (RID), 24329596 (EID)
Grant Number: L40 HD073901, P50 HD052120, P50HD052120, R305F100005
Publication Note: This NIH-funded author manuscript originally appeared in PubMed Central at
Subject(s): Biomedical Research/methods
Data Interpretation, Statistical
Human Development
Regression Analysis
Persistent Link to This Record:
Host Institution: FSU
Is Part Of: Child development.
Issue: iss. 3, vol. 85

Choose the citation style.
Petscher, Y., & Logan, J. A. R. (2014). Quantile regression in the study of developmental sciences. Child Development. Retrieved from