Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 8 |
Descriptor
Source
Author
Publication Type
Education Level
| Higher Education | 1 |
Audience
| Researchers | 18 |
Location
| Netherlands | 4 |
| Australia | 1 |
| Belgium | 1 |
| California | 1 |
| Denmark | 1 |
| Florida | 1 |
| Illinois (Chicago) | 1 |
| Japan | 1 |
| United Kingdom (Scotland) | 1 |
| United States | 1 |
| West Germany | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewedPoon, Wai-Yin; Lee, Sik-Yum – Psychometrika, 1987
Reparameterization is used to find the maximum likelihood estimates of parameters in a multivariate model having some component variable observable only in polychotomous form. Maximum likelihood estimates are found by a Fletcher Powell algorithm. In addition, the partition maximum likelihood method is proposed and illustrated. (Author/GDC)
Descriptors: Correlation, Estimation (Mathematics), Latent Trait Theory, Mathematical Models
Peer reviewedThissen, David; Steinberg, Lynne – Psychometrika, 1986
This article organizes models for categorical item response data into three distinct classes. "Difference models" are appropriate for ordered responses, "divide-by-total" models for either ordered or nominal responses, and "left-side added" models for multiple-choice responses with guessing. Details of the taxonomy…
Descriptors: Classification, Item Analysis, Latent Trait Theory, Mathematical Models
Peer reviewedBloxom, Bruce – Psychometrika, 1985
A constrained quadratic spline is proposed as an estimator of the hazard function of a random variable. A maximum penalized likelihood procedure is used to fit the estimator to a sample of psychological response times. (Author/LMO)
Descriptors: Estimation (Mathematics), Goodness of Fit, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedMuthen, Bengt; Joreskog, Karl G. – Evaluation Review, 1983
Selectivity problems are discussed in terms of a general model that is estimated by the maximum likelihood method. Both single-group and multiple-group analyses are considered. An extension of the general model to latent variable models is discussed. (Author/PN)
Descriptors: Mathematical Models, Maximum Likelihood Statistics, Quasiexperimental Design, Research Methodology
Peer reviewedWilcox, Rand R. – Educational and Psychological Measurement, 1980
Technical problems in achievement testing associated with using latent structure models to estimate the probability of guessing correct responses by examinees is studied; also the lack of problems associated with using Wilcox's formula score. Maximum likelihood estimates are derived which may be applied when items are hierarchically related.…
Descriptors: Guessing (Tests), Item Analysis, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedKiers, Henk A. L. – Psychometrika, 1997
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. The approach consists of iteratively performing steps of existing algorithms for ordinary least squares fitting of the same model and is based on maximizing a function that majorizes WLS loss function. (Author/SLD)
Descriptors: Algorithms, Goodness of Fit, Least Squares Statistics, Mathematical Models
Peer reviewedClogg, Clifford C.; And Others – Journal of Educational Statistics, 1992
Methods for assessing collapsibility in regression problems are described, including possible extensions to the class of generalized linear models. These procedures, with terminology borrowed from the contingency table field, can be used in experimental settings or nonexperimental settings where two models viewed as alternative explanations are…
Descriptors: Comparative Analysis, Equations (Mathematics), Mathematical Models, Maximum Likelihood Statistics
Peer reviewedCritchlow, Douglas E.; Fligner, Michael A. – Psychometrika, 1991
A variety of paired comparison, triple comparison, and ranking experiments are discussed as generalized linear models. All such models can be easily fit by maximum likelihood using the GLIM computer package. Examples are presented for a variety of cases using GLIM. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Equations (Mathematics)
Peer reviewedFava, Joseph L.; Velicer, Wayne F. – Multivariate Behavioral Research, 1992
Effects of overextracting factors and components within and between maximum likelihood factor analysis and principal components analysis were examined through computer simulation of a range of factor and component patterns. Results demonstrate similarity of component and factor scores during overextraction. Overall, results indicate that…
Descriptors: Computer Simulation, Correlation, Factor Analysis, Mathematical Models
Muthen, Bengt; Masyn, Katherine – Journal of Educational and Behavioral Statistics, 2005
This article proposes a general latent variable approach to discrete-time survival analysis of nonrepeatable events such as onset of drug use. It is shown how the survival analysis can be formulated as a generalized latent class analysis of event history indicators. The latent class analysis can use covariates and can be combined with the joint…
Descriptors: Drug Use, Maximum Likelihood Statistics, Computer Software, Aggression
McKinley, Robert L.; Reckase, Mark D. – 1983
Item response theory (IRT) has proven to be a very powerful and useful measurement tool. However, most of the IRT models that have been proposed, and all of the models commonly used, require the assumption of unidimensionality, which prevents their application to a wide range of tests. The few models that have been proposed for use with…
Descriptors: Estimation (Mathematics), Latent Trait Theory, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedDouglas, Graham A. – Psychometrika, 1978
A goodness of fit test presented by Andersen (EJ 143 939) is shown to be incorrect. The correct test is described and a re-analysis of Andersen's data is provided. (Author/CTM)
Descriptors: Goodness of Fit, Individual Differences, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedAndersen, Erling B. – Psychometrika, 1978
Graham Douglas' claims (TM 503 496) that the X2-test statistics of the paper, "Paired Comparisons with Individual Differences" (EJ 143 939), are incorrect are acknowledged to be justified (Author/CTM)
Descriptors: Goodness of Fit, Individual Differences, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedVillegas, C. – Journal of Multivariate Analysis, 1976
A multiple time series is defined as the sum of an autoregressive process on a line and independent Gaussian white noise or a hyperplane that goes through the origin and intersects the line at a single point. This process is a multiple autoregressive time series in which the regression matrices satisfy suitable conditions. For a related article…
Descriptors: Mathematical Models, Matrices, Maximum Likelihood Statistics, Orthogonal Rotation
Peer reviewedBrady, Henry E. – Psychometrika, 1985
The properties of nonmetric multidimensional scaling one explored by specifying statistical models, proving statistical consistency, and devloping hypothesis testing procedures. Statistical models with errors in the dependent and independent variables are described for quantitative and qualitative data. (Author/LMO)
Descriptors: Goodness of Fit, Hypothesis Testing, Mathematical Models, Maximum Likelihood Statistics

Direct link
