ERIC Number: EJ1027472
Record Type: Journal
Publication Date: 2014
Abstractor: As Provided
Quantile Regression in the Study of Developmental Sciences
Petscher, Yaacov; Logan, Jessica A. R.
Child Development, v85 n3 p861-881 May-Jun 2014
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.
Descriptors: Regression (Statistics), Evaluation Methods, Databases, Longitudinal Studies, Research Methodology, Inferences, Child Development, Developmental Psychology
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: R305F100005