发育科学研究中的分位数回归
Quantile regression in the study of developmental sciences.
作者信息
Petscher Yaacov, Logan Jessica A R
机构信息
Florida Center for Reading Research Florida State University.
Ohio State University.
出版信息
Child Dev. 2014 May-Jun;85(3):861-881. doi: 10.1111/cdev.12190. Epub 2013 Dec 13.
Abstract
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.
摘要
线性回归分析是发展研究中应用最广泛的技术之一，但它只能估计预测变量与结果之间的平均关系。本研究介绍了分位数回归，它能估计预测变量与结果之间的关系，而且是针对结果分布的多个点进行估计。利用“高中及以后”和“美国持续影响研究”数据库中的数据，展示了分位数回归，并在考虑以下模型时将其与线性回归进行对比：(a) 一个连续预测变量；(b) 一个二分预测变量；(c) 一个连续预测变量和一个二分预测变量；(d) 纵向应用。每个例子的结果都显示了使用线性回归或分位数回归可能得出的不同推断。
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