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Pruzek, Robert M.; Rabinowitz, Stanley N. – American Educational Research Journal, 1981
Simple modifications of principal component methods are described that have distinct advantages for structural analysis of relations among educational and psychological variables. The methods are contrasted theoretically and empirically with conventional principal component methods and with maximum likelihood factor analysis. (Author/GK)
Descriptors: Factor Analysis, Mathematical Models, Maximum Likelihood Statistics, Multivariate Analysis
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Novick, Melvin R. – Psychometrika, 1980
Modern statistics are considered as a branch of psychometrics and the question of how the central problems of statistics can be resolved using psychometric methods is investigated. Methods developed in the fields of test theory, scaling, and factor analysis are related to principle problems of modern statistical theory and method. (Author/JKS)
Descriptors: Bayesian Statistics, Computers, Maximum Likelihood Statistics, Measurement Techniques
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Bedrick, Edward J.; Breslin, Frederick C. – Psychometrika, 1996
Simple noniterative estimators of the polyserial correlation coefficient are developed by exploiting a general relationship between the polyserial correlation and the point polyserial correlation to give extensions of the biserial estimators of K. Pearson (1909), H. E. Brogden (1949), and F. M. Lord (1963) to the multicategory setting. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Maximum Likelihood Statistics, Sample Size
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Jedidi, Kamel; And Others – Structural Equation Modeling, 1996
An Expectation-Maximization (EM) algorithm in a maximum likelihood framework is developed to estimate finite mixtures of multivariate regression and simultaneous equation models with multiple endogenous variables. A dataset with cross-sectional observations for a diverse sample of businesses illustrates the semiparametric approach. (SLD)
Descriptors: Estimation (Mathematics), Maximum Likelihood Statistics, Multivariate Analysis, Regression (Statistics)
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Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M. – Structural Equation Modeling, 2002
Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…
Descriptors: Maximum Likelihood Statistics, Regression (Statistics), Simulation, Structural Equation Models
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Roberts, James S.; Donoghue, John R.; Laughlin, James E. – Applied Psychological Measurement, 2002
Investigated the data demands associated with the marginal maximum likelihood (MML) expected a posterior (EAP) methodology and the precision of the resulting parameter estimates when data fit the underlying model through simulation. Also studied the extent to which a misspecified prior distribution would affect the item and person parameter…
Descriptors: Estimation (Mathematics), Maximum Likelihood Statistics, Models, Research Methodology
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Poon, Wai-Yin; Chan, Wai – Psychometrika, 2002
Developed diagnostic measures to identify observations in Thurstonian models for ranking data that unduly influence parameter estimates obtained by the partition maximum likelihood approach of W. Chan and P. Bender (1998). (SLD)
Descriptors: Diagnostic Tests, Equations (Mathematics), Estimation (Mathematics), Maximum Likelihood Statistics
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DeMars, Christine – Applied Measurement in Education, 2002
Simulated items from two test forms using joint maximum likelihood estimation (JMLE) and marginal maximum likelihood estimation (MML) in the vertical equating situation (using an anchor test) when data were nonrandomly missing. Under MML, when the different ability parameters of students were not taken into account, the item difficulty parameters…
Descriptors: Ability, Equated Scores, Estimation (Mathematics), Maximum Likelihood Statistics
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Pigott, Therese D. – Educational Research and Evaluation: An International Journal on Theory and Practice, 2001
Reviews methods for handling missing data in a research study. Model-based methods, such as maximum likelihood using the EM algorithm and multiple imputation, hold more promise than ad hoc methods. Although model-based methods require more specialized computer programs and assumptions about the nature of missing data, these methods are appropriate…
Descriptors: Computer Software, Mathematical Models, Maximum Likelihood Statistics, Research Methodology
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Andersen, Erling B. – Journal of Educational and Behavioral Statistics, 2002
Presents a simple result concerning variances of maximum likelihood (ML) estimators. The result allows for construction of residual diagrams to evaluate whether ML estimators derived from independent samples can be assumed to be equal apart from random errors. Applies this result to the polytomous Rasch model. (SLD)
Descriptors: Diagrams, Estimation (Mathematics), Item Response Theory, Maximum Likelihood Statistics
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Winsberg, Suzanne; Carroll, J. Douglas – Psychometrika, 1989
An Extended Two-Way Euclidean Multidimensional Scaling (MDS) model that assumes both common and specific dimensions is described and contrasted with the "standard" (Two-Way) MDS model. Illustrations with both artificial and real data on the judged similarity of nations are provided. (TJH)
Descriptors: Algorithms, Chi Square, Maximum Likelihood Statistics, Multidimensional Scaling
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Smit, Arnold; Kelderman, Henk – Journal of Outcome Measurement, 2000
Proposes an estimation method for the Rasch model that is based on the pseudolikelihood theory of B. Arnold and D. Strauss (1988). Simulation results show great similarity between estimates from this method with those from conditional maximum likelihood and unconditional maximum likelihood estimates for the item parameters of the Rasch model. (SLD)
Descriptors: Estimation (Mathematics), Item Response Theory, Maximum Likelihood Statistics, Simulation
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Vermunt, Jeroen K. – Applied Psychological Measurement, 2001
Presents a general class of ordinal logit models that specifies equality and inequality constraints on sums of conditional response probabilities. Uses maximum likelihood to estimate these models, making their assumptions testable with likelihood-ratio statistics. Illustrates the proposed models with an example using reported adult crying…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Models, Nonparametric Statistics
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Bertoli-Barsotti, Lucio – Psychometrika, 2005
A necessary and sufficient condition is given in this paper for the existence and uniqueness of the maximum likelihood (the so-called joint maximum likelihood) estimate of the parameters of the Partial Credit Model. This condition is stated in terms of a structural property of the pattern of the data matrix that can be easily verified on the basis…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Mathematical Models, Psychometrics
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Christensen, Karl Bang; Kreiner, Svend – Applied Psychological Measurement, 2007
Many statistical tests are designed to test the different assumptions of the Rasch model, but only few are directed at detecting multidimensionality. The Martin-Lof test is an attractive approach, the disadvantage being that its null distribution deviates strongly from the asymptotic chi-square distribution for most realistic sample sizes. A Monte…
Descriptors: Item Response Theory, Monte Carlo Methods, Testing, Models
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