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Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas – Psychometrika, 2013
Most dichotomous item response models share the assumption of latent monotonicity, which states that the probability of a positive response to an item is a nondecreasing function of a latent variable intended to be measured. Latent monotonicity cannot be evaluated directly, but it implies manifest monotonicity across a variety of observed scores,…
Descriptors: Item Response Theory, Statistical Inference, Probability, Psychometrics
van Ginkel, Joost R.; van der Ark, L. Andries; Sijtsma, Klaas – Multivariate Behavioral Research, 2007
The performance of five simple multiple imputation methods for dealing with missing data were compared. In addition, random imputation and multivariate normal imputation were used as lower and upper benchmark, respectively. Test data were simulated and item scores were deleted such that they were either missing completely at random, missing at…
Descriptors: Evaluation Methods, Psychometrics, Item Response Theory, Scores

Sijtsma, Klaas; Molenaar, Ivo W. – Psychometrika, 1987
Three methods for estimating reliability are studied within the context of nonparametric item response theory. Two were proposed originally by Mokken and a third is developed in this paper. Using a Monte Carlo strategy, these three estimation methods are compared with four "classical" lower bounds to reliability. (Author/JAZ)
Descriptors: Estimation (Mathematics), Latent Trait Theory, Measurement Techniques, Monte Carlo Methods

Sijtsma, Klaas; Meijer, Rob R. – Psychometrika, 2001
Studied the use of the person response function (PRF) for identifying nonfitting item score patterns. Proposed a person-fit method reformulated in a nonparametric item response theory (IRT) context. Conducted a simulation study to compare the use of the PRF with a person-fit statistic, resulting in the conclusion that the PRF can be used as a…
Descriptors: Item Response Theory, Monte Carlo Methods, Nonparametric Statistics, Scores
Meijer, Rob R.; Sijtsma, Klaas – 1994
Methods for detecting item score patterns that are unlikely (aberrant) given that a parametric item response theory (IRT) model gives an adequate description of the data or given the responses of the other persons in the group are discussed. The emphasis here is on the latter group of statistics. These statistics can be applied when a…
Descriptors: Foreign Countries, Identification, Item Response Theory, Nonparametric Statistics

Meijer, Rob R.; Sijtsma, Klaas – Applied Measurement in Education, 1995
Methods for detecting item score patterns that are unlikely, given that a parametric item response theory model gives an adequate description of the data or given the responses of other persons in the group, are discussed. The use of person-fit statistics in empirical data analysis is briefly discussed. (SLD)
Descriptors: Identification, Item Response Theory, Nonparametric Statistics, Patterns in Mathematics

Sijtsma, Klaas – Applied Psychological Measurement, 1998
Reviews developments in nonparametric item-response theory (NIRT), from its historic origins in item-response theory (IRT) and scale analysis to new theoretical results for practical test construction. Discusses theoretical results from NIRT often relevant to IRT. Contains 134 references. (SLD)
Descriptors: Item Response Theory, Nonparametric Statistics, Research Methodology, Scores
Meijer, Rob R.; Sijtsma, Klaas – 1999
Methods are discussed that can be used to investigate the fit of an item score pattern to a test model. Model-based tests and personality inventories are administered to more than 100 million people a year and, as a result, individual fit is of great concern. Item Response Theory (IRT) modeling and person-fit statistics that are formulated in the…
Descriptors: Evaluation Methods, Goodness of Fit, Item Response Theory, Personality Measures