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Peer reviewedvan den Wollenberg, Arnold L.; And Others – Applied Psychological Measurement, 1988
The unconditional--simultaneous--maximum likelihood (UML) estimation procedure for the one-parameter logistic model produces biased estimators. The UML method is inconsistent and is not a good alternative to conditional maximum likelihood method, at least with small numbers of items. The minimum Chi-square estimation procedure produces unbiased…
Descriptors: Computer Simulation, Estimation (Mathematics), Maximum Likelihood Statistics, Reliability
Peer reviewedFischer, Gerhard H. – Applied Psychological Measurement, 2003
Compared approaches to determining the precision of gain scores: (1) the asymptotic normal distribution of the maximum likelihood estimator of the person parameter; and (2) the exact conditional distribution of the gain score. Use of three data sets illustrates that these methods yield more relevant and more detailed information than traditional…
Descriptors: Estimation (Mathematics), Item Response Theory, Maximum Likelihood Statistics, Reliability
Peer reviewedJackson, Dennis L. – Structural Equation Modeling, 2001
Investigated the assumption that determining an adequate sample size in structural equation modeling can be aided by considering the number of parameters to be estimated. Findings from maximum likelihood confirmatory factor analysis support previous research on the effect of sample size, measured variable reliability, and the number of measured…
Descriptors: Estimation (Mathematics), Maximum Likelihood Statistics, Monte Carlo Methods, Reliability
Peer reviewedNicewander, W. Alan; Thomasson, Gary L. – Applied Psychological Measurement, 1999
Derives three reliability estimates for the Bayes modal estimate (BME) and the maximum-likelihood estimate (MLE) of theta in computerized adaptive tests (CATs). Computes the three reliability estimates and the true reliabilities of both BME and MLE for seven simulated CATs. Results show the true reliabilities for BME and MLE to be nearly identical…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
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
