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NCJ Number: 72750 Find in a Library
Title: Robust Estimation of Ability in the Rasch Model (From Robust Estimation in Latent Trait Analysis - Final Report, 1980 - See NCJ-72747)
Author(s): H Wainer; B D Wright
Corporate Author: Bureau of Social Science Research, Inc
United States of America
Date Published: 1980
Page Count: 43
Sponsoring Agency: Bureau of Social Science Research, Inc
Washington, DC 20036
National Institute of Justice/
Rockville, MD 20849
US Dept of Justice
Washington, DC 20531
Grant Number: 78-NI-AX-0047
Sale Source: National Institute of Justice/
NCJRS paper reproduction
Box 6000, Dept F
Rockville, MD 20849
United States of America
Document: PDF
Type: Statistics
Language: English
Country: United States of America
Annotation: Formulations aimed at dealing with noise data in estimating ability parameters in the Rasch Model without a reparameterization are tested through a Monte Carlo simulation.
Abstract: Estimating ability parameters in latent trait models in general and in the Rasch Model in particular is almost always hampered by noise in the data. This noise can be caused by guessing, inattention to easy questions, and other factors which are unrelated to ability. It was found that although no one of the tested schemes is uniformly superior to all others, a robustified Jackknife is generally the best scheme; it was also very efficient for tests with 40 or fewer items. The Jackknifing scheme is proposed for estimating ability for practical work. Tabular data and 22 references are provided. (Author abstract modified)
Index Term(s): Mathematical modeling; Prediction; Statistical analysis; Testing and measurement
To cite this abstract, use the following link:
http://www.ncjrs.gov/App/publications/abstract.aspx?ID=72750

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