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Glas, Cees A. W.; van der Linden, Wim J. – 2001
To reduce the cost of item writing and to enhance the flexibility of item presentation, items can be generated by item-cloning techniques. An important consequence of cloning is that it may cause variability on the item parameters. Therefore, a multilevel item response model is presented in which it is assumed that the item parameters of a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Costs
Nevitt, Jonathan – 2000
Structural equation modeling (SEM) attempts to remove the negative influence of measurement error and allows for investigation of relationships at the level of the underlying constructs of interest. SEM has been regarded as a "large sample" technique since its inception. Recent developments in SEM, some of which are currently available…
Descriptors: Error of Measurement, Goodness of Fit, Maximum Likelihood Statistics, Monte Carlo Methods
Peer reviewedMorgan, Anne; Wainer, Howard – Journal of Educational Statistics, 1980
Two estimation procedures for the Rasch Model of test analysis are reviewed in detail, particularly with respect to new developments that make the more statistically rigorous conditional maximum likelihood estimation practical for use with longish tests. (Author/JKS)
Descriptors: Error of Measurement, Latent Trait Theory, Maximum Likelihood Statistics, Psychometrics
Peer reviewedFischer, Gerhard H. – Psychometrika, 1989
The linear logistic model with relaxed assumption is extended to designs with any number of time points or with different sets of items presented on different occasions, provided that one unidimensional subscale is available per latent trait. A sample application is presented. (SLD)
Descriptors: Data Interpretation, Equations (Mathematics), Estimation (Mathematics), Item Response Theory
Peer reviewedMeredith, William; Tisak, John – Psychometrika, 1990
A model based on latent trait theory, with maximum likelihood parameter estimates and associated asymptotic tests, is presented. Latent curve analysis is a method for representing development and is an alternative to repeated measures analysis of variance and first-order auto-regressive models. (SLD)
Descriptors: Analysis of Variance, Estimation (Mathematics), Item Response Theory, Mathematical Models
Peer reviewedSorbom, Dag – Psychometrika, 1989
A modification index is presented to aid in reformulating hypothetical models rejected after analysis of empirical data. This index is an improvement over the one in the LISREL V computer program in that it takes into account changes in all parameters of the model when one parameter is freed. (SLD)
Descriptors: Equations (Mathematics), Evaluation Methods, Factor Analysis, Hypothesis Testing
Peer reviewedBock, R. Darrell; And Others – Applied Psychological Measurement, 1988
A method of item factor analysis is described, which is based on Thurstone's multiple-factor model and implemented by marginal maximum likelihood estimation and the EM algorithm. Also assessed are the statistical significance of successive factors added to the model, provisions for guessing and omitted items, and Bayes constraints. (TJH)
Descriptors: Algorithms, Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics)
Peer reviewedRaaijmakers, Jeroen G. W.; Pieters, Jo P. M. – Psychometrika, 1987
Functional and structural relationship alternatives to the standard "F"-test for analysis of covariance (ANCOVA) are discussed for cases when the covariate is measured with error. An approximate statistical test based on the functional relationship approach is preferred on the basis of Monte Carlo simulation results. (SLD)
Descriptors: Analysis of Covariance, Computer Simulation, Error of Measurement, Hypothesis Testing
Peer reviewedLevine, Michael V.; Drasgow, Fritz – Psychometrika, 1988
Some examinees' test-taking behavior may be so idiosyncratic that their test scores are not comparable to those of more typical examinees. A new theoretical approach to appropriateness measurement is proposed that specifies a likelihood ratio test and an efficient computer algorithm for computing the test statistic. (TJH)
Descriptors: Algorithms, Computer Simulation, Latent Trait Theory, Maximum Likelihood Statistics
Peer reviewedSamejima, Fumiko – Psychometrika, 1994
Using the constant information model, constant amounts of test information, and a finite interval of ability, simulated data were produced for 8 ability levels and 20 numbers of test items. Analyses suggest that it is desirable to consider modifying test information functions when they measure accuracy in ability estimation. (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Computer Simulation
Peer reviewedStorms, Gert; Delbeke, Luc – Psychometrika, 1992
Y. Takane and J. Sergent developed a model (MAXRT) for scaling same/different judgments and response times (RTs) simultaneously. The adequacy of the assumption that RTs are distributed log-normally is considered, and the effect of a violation of this assumption is investigated via a computer simulation. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Goodness of Fit, Mathematical Models
Peer reviewedHarwell, Michael R.; Baker, Frank B. – Applied Psychological Measurement, 1991
Previous work on the mathematical and implementation details of the marginalized maximum likelihood estimation procedure is extended to encompass the marginalized Bayesian procedure for estimating item parameters of R. J. Mislevy (1986) and to communicate this procedure to users of the BILOG computer program. (SLD)
Descriptors: Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics), Item Response Theory
Peer reviewedStone, 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
Peer reviewedMislevy, Robert J.; Verhelst, Norman – Psychometrika, 1990
A model is presented for item responses when different subjects use different strategies, but only responses--not choice of strategy--can be observed. Substantive theory is used to differentiate the likelihoods of response vectors under a fixed set of strategies, and response probabilities are modeled via item parameters for each strategy. (TJH)
Descriptors: Algorithms, Guessing (Tests), Item Response Theory, Mathematical Models
Peer reviewedMolenaar, Peter C. M.; Nesselroade, John R. – Multivariate Behavioral Research, 1998
Pseudo-Maximum Likelihood (p-ML) and Asymptotically Distribution Free (ADF) estimation methods for estimating dynamic factor model parameters within a covariance structure framework were compared through a Monte Carlo simulation. Both methods appear to give consistent model parameter estimates, but only ADF gives standard errors and chi-square…
Descriptors: Chi Square, Comparative Analysis, Error of Measurement, Estimation (Mathematics)


