Optimal Item Discrimination and Maximum Information for Logistic IRT Models
- 1 March 1999
- journal article
- Published by SAGE Publications in Applied Psychological Measurement
- Vol. 23 (1) , 31-40
- https://doi.org/10.1177/01466219922031167
Abstract
Items with the highest discrimination parameter values in a logistic item response theory model do not necessarily give maximum information. This paper derives discrimination parameter values, as functions of the guessing parameter and distances between person parameters and item difficulty, that yield maximum information for the three-parameter logistic item response theory model. An upper bound for information as a function of these parameters is also derived. An algorithm is suggested for the maximum information item selection criterion for adaptive testing and is compared with a full bank search algorithm.Keywords
This publication has 5 references indexed in Scilit:
- Some Critical Observations of the Test Information Function as a Measure of Local Accuracy in Ability EstimationPsychometrika, 1994
- A Method for Severely Constrained Item Selection in Adaptive TestingApplied Psychological Measurement, 1993
- A Model and Heuristic For Solving Very Large Item Selection ProblemsApplied Psychological Measurement, 1993
- Results of Item Parameter Estimation Using LOGIST 5 on Simulated Data.Published by Defense Technical Information Center (DTIC) ,1984
- The attenuation paradox in test theory.Psychological Bulletin, 1954