Estimation of Latent Group Effects.

Abstract

Conventional methods of multivariate normal analysis do not apply when the variables of interest are not observed directly, but must be inferred from fallible or incomplete data. For example, responses to mental test items may depend upon latent aptitude variables, which modeled in turn as functions of demographic effects in the population. A method of estimating such effects by means of marginal maximum likelihood, implemented by means of an EM algorithm, is proposed. Asymptotic standard errors, likelihood ratio tests of alternative models, and computing approximations are provided. The procedures are illustrated with data for tests from the Armed Services Vocational Aptitude Battery administered to a national probability sample of American youth. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1983
Accession Number
ADA139299

Entities

People

  • R. J. Mislevy

Organizations

  • NORC at the University of Chicago

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Applied Psychology
  • Biological Sciences
  • Cognition
  • Department Of Defense
  • Equations
  • Human Resources
  • Illinois
  • Military Research
  • Observation
  • Personnel Management
  • Probability
  • Psychology
  • Random Variables
  • Standards
  • United States
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Instructional Design and Training Evaluation.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference