A Nonparametric Multidimensional IRT Approach with Applications to Ability Estimation and Test Bias.

Abstract

A determined case is made for the use of a nonparametric multidimensional monotonic IRT modeling framework with local independence replaced by the less restrictive assumption of essential independence. The concept of essential dimensionality is then introduced to count the number of dominant latent dimensions. Consequences of this more general approach include the consistent estimation of ability on a common scale using a natural class of estimators, uniqueness of the latent ability when essential unidimensionality holds, a theoretical treatment of test bias, an IRT based notion of validity, and a reassessment of the importance of the concept of item parameter invariance. Keywords: Local independence; Essential independence; Essential trait; Intrinsic ability scale; Marginal item response function; Latent dimensionality; Multidimensionality; Essential dimensionality; Essential unidimensionality; Item response theory; Latent trait theory; Ability estimation; Consistent estimation; Item parameter invariance; Validity; Linear formula scoring; Nonparametric.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1988
Accession Number
ADA194212

Entities

People

  • William Stout

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Data Science
  • Educational Psychology
  • Estimators
  • Information Science
  • Invariance
  • Measurement
  • Military Research
  • Personnel Management
  • Probability
  • Psychology
  • Random Variables
  • Standards
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Tests
  • Statistics
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Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis
  • Psychometric Testing or Psychological Assessment.