Sampling Variances and Covariances of Parameter Estimates in Item Response Theory.

Abstract

This paper develops a possible method for computing the asymptotic sampling variance-covariance matrix of joint maximum likelihood estimates in item response theory when both item parameters and abilities are unknown. For a set of artificial data, results are compared with empirical values; also with the variance-covariance matrices found by the usual formulas for the case where the abilities are known, or where the item parameters are known. The results are consistent with the conjecture that the new method is asymptotically correct except for errors due to grouping. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1982
Accession Number
ADA119609

Entities

People

  • Frederic M. Lord
  • Marilyn S. Wingersky

Organizations

  • Educational Testing Service

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Behavioral Sciences
  • Cognition
  • Computers
  • Covariance
  • Data Science
  • Education
  • Errors
  • Goodness Of Fit Tests
  • Information Science
  • Military Research
  • Personnel Management
  • Psychology
  • Social Sciences
  • Standards
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.