Estimation of nonlinear learning models

Published

Journal Article

The article develops the structure and estimates the parameters of a nonlinear learning model applicable to research designs in which students are tested at the beginning and end of a course of study. A student’s precourse score is an error-ridden proxy for his precourse aptitude. As a remedy for this problem, the article combines a probit model of test score outcomes, a learning function, and a linear equation relating aptitude to demographic characteristics to deduce the exact test score distribution. An empirical example of maximum likelihood estimation of the model’s parameters is presented. © 1982 Taylor & Francis Group, LLC.

Full Text

Duke Authors

Cited Authors

  • Salemi, MK; Tauchen, GE

Published Date

  • January 1, 1982

Published In

Volume / Issue

  • 77 / 380

Start / End Page

  • 725 - 731

Electronic International Standard Serial Number (EISSN)

  • 1537-274X

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1080/01621459.1982.10477877

Citation Source

  • Scopus