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The Effect of Test Length and IRT Model on the Distribution and Stability of Three Appropriateness Indexes.
Peer reviewed Peer reviewed
Noonan, Brian W.; And Others – Applied Psychological Measurement, 1992
Studied the extent to which three appropriateness indexes, Z(sub 3), ECIZ4, and W, are well standardized in a Monte Carlo study. The ECIZ4 most closely approximated a normal distribution, and its skewness and kurtosis were more stable and less affected by test length and item response theory model than the others. (SLD)
Descriptors: Comparative Analysis, Item Response Theory, Mathematical Models, Maximum Likelihood Statistics
Recovery of Marginal Maximum Likelihood Estimates in the Two-Parameter Logistic Response Model: An Evaluation of MULTILOG.
Peer reviewed Peer reviewed
Stone, Clement A. – Applied Psychological Measurement, 1992
Monte Carlo methods are used to evaluate marginal maximum likelihood estimation of item parameters and maximum likelihood estimates of theta in the two-parameter logistic model for varying test lengths, sample sizes, and assumed theta distributions. Results with 100 datasets demonstrate the methods' general precision and stability. Exceptions are…
Descriptors: Computer Software Evaluation, Estimation (Mathematics), Mathematical Models, Maximum Likelihood Statistics
The Influence of Test Characteristics on the Detection of Aberrant Response Patterns.
Peer reviewed Peer reviewed
Reise, Steven P.; Due, Allan M. – Applied Psychological Measurement, 1991
Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)
Descriptors: Algorithms, Computer Simulation, Item Response Theory, Mathematical Models
The Standard Errors of the Feldt-Gilmer Congeneric Reliability Coefficients: Iowa Testing Programs Occasional Papers. Number 31.
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Gilmer, Jerry S.; Feldt, Leonard S. – 1982
The Feldt-Gilmer congeneric reliability coefficients make it possible to estimate the reliability of a test composed of parts of unequal, unknown length. The approximate standard errors of the Feldt-Gilmer coefficients are derived via a method using the multivariate Taylor's expansion. Monte Carlo simulation is employed to corroborate the…
Descriptors: Educational Testing, Error of Measurement, Mathematical Formulas, Mathematical Models
A Monte Carlo Study of Marginal Maximum Likelihood Parameter Estimates for the Graded Model.
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Ankenmann, Robert D.; Stone, Clement A. – 1992
Effects of test length, sample size, and assumed ability distribution were investigated in a multiple replication Monte Carlo study under the 1-parameter (1P) and 2-parameter (2P) logistic graded model with five score levels. Accuracy and variability of item parameter and ability estimates were examined. Monte Carlo methods were used to evaluate…
Descriptors: Computer Simulation, Estimation (Mathematics), Item Bias, Mathematical Models
Thin versus Thick Matching in the Mantel-Haenszel Procedure for Detecting DIF.
Peer reviewed Peer reviewed
Donoghue, John R.; Allen, Nancy L. – Journal of Educational Statistics, 1993
Forming the matching variable for the Mantel-Haenszel differential item functioning (DIF) procedure through use of the total score as the matching variable (thin) and forming the matching variable by pooling total score levels (thick) were compared in a Monte Carlo study. Reasons thick matching is superior are discussed. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Graphs
Effect of the Guessing Parameter on the Estimation of the Item Discrimination and Difficulty Parameters When Three-Parameter Logistic Model Is Assumed.
Samejima, Fumiko – 1986
Item analysis data fitting the normal ogive model were simulated in order to investigate the problems encountered when applying the three-parameter logistic model. Binary item tests containing 10 and 35 items were created, and Monte Carlo methods simulated the responses of 2,000 and 500 examinees. Item parameters were obtained using Logist 5.…
Descriptors: Computer Simulation, Difficulty Level, Guessing (Tests), Item Analysis