Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 0 |
Since 2006 (last 20 years) | 6 |
Descriptor
Scores | 15 |
Models | 7 |
Mathematical Models | 5 |
Statistical Analysis | 4 |
Computation | 3 |
Factor Analysis | 3 |
Hypothesis Testing | 3 |
Psychometrics | 3 |
Structural Equation Models | 3 |
Comparative Analysis | 2 |
Correlation | 2 |
More ▼ |
Source
Multivariate Behavioral… | 15 |
Author
Fava, Joseph L. | 2 |
Velicer, Wayne F. | 2 |
Anguiano-Carrasco, Cristina | 1 |
Brown, Anna | 1 |
Dimitrov, Dimiter M. | 1 |
Ferrando, Pere J. | 1 |
Grimm, Kevin J. | 1 |
Haberman, Shelby J. | 1 |
Hau, Kit-Tai | 1 |
Jo, Booil | 1 |
Kaplan, David | 1 |
More ▼ |
Publication Type
Journal Articles | 15 |
Reports - Evaluative | 6 |
Reports - Research | 6 |
Reports - Descriptive | 3 |
Education Level
Elementary Education | 1 |
Grade 1 | 1 |
Grade 3 | 1 |
Primary Education | 1 |
Audience
Location
Texas | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Block Design Test | 1 |
What Works Clearinghouse Rating
Wang, Lijuan; Grimm, Kevin J. – Multivariate Behavioral Research, 2012
Reliabilities of the two most widely used intraindividual variability indicators, "ISD[superscript 2]" and "ISD", are derived analytically. Both are functions of the sizes of the first and second moments of true intraindividual variability, the size of the measurement error variance, and the number of assessments within a burst. For comparison,…
Descriptors: Reliability, Statistical Analysis, Measurement, Models
Sinharay, Sandip; Puhan, Gautam; Haberman, Shelby J. – Multivariate Behavioral Research, 2010
Diagnostic scores are of increasing interest in educational testing due to their potential remedial and instructional benefit. Naturally, the number of educational tests that report diagnostic scores is on the rise, as are the number of research publications on such scores. This article provides a critical evaluation of diagnostic score reporting…
Descriptors: Educational Testing, Scores, Reports, Psychometrics
Jo, Booil; Stuart, Elizabeth A.; MacKinnon, David P.; Vinokur, Amiram D. – Multivariate Behavioral Research, 2011
Mediation analysis uses measures of hypothesized mediating variables to test theory for how a treatment achieves effects on outcomes and to improve subsequent treatments by identifying the most efficient treatment components. Most current mediation analysis methods rely on untested distributional and functional form assumptions for valid…
Descriptors: Probability, Scores, Statistical Analysis, Computation
Thoemmes, Felix J.; West, Stephen G. – Multivariate Behavioral Research, 2011
In this article we propose several modeling choices to extend propensity score analysis to clustered data. We describe different possible model specifications for estimation of the propensity score: single-level model, fixed effects model, and two random effects models. We also consider both conditioning within clusters and conditioning across…
Descriptors: Probability, Scores, Statistical Analysis, Models
Ferrando, Pere J.; Anguiano-Carrasco, Cristina – Multivariate Behavioral Research, 2009
This article proposes a model-based multiple-group procedure for assessing the impact of faking on personality measures and the scores derived from these measures. The assessment is at the item level and the base model, which is intended for binary items, can be parameterized both as an Item Response Theory (IRT) model and as an Item…
Descriptors: Personality, Personality Measures, Item Response Theory, Deception
Maydeu-Olivares, Alberto; Brown, Anna – Multivariate Behavioral Research, 2010
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…
Descriptors: Item Response Theory, Rating Scales, Models, Comparative Analysis

Marsh, Herbert W.; Hau, Kit-Tai – Multivariate Behavioral Research, 2002
Evaluated multilevel models of growth and change in relation to regression toward the mean artifacts (RTMAs), using simulated data to represent students nested within schools for which there were initial school differences due to selection based on pretest achievement scores. Results demonstrate that multilevel growth models provide no protection…
Descriptors: Academic Achievement, Change, Models, Scores

Kaplan, David – Multivariate Behavioral Research, 1999
Proposes an extension of the propensity score adjustment method to the analysis of group differences on latent variable models. Uses multiple indicators-multiple causes (MIMIC) structural equation modeling to test hypotheses about treatment group differences. Discusses the role of factorial invariance as it relates to this approach. (SLD)
Descriptors: Groups, Hypothesis Testing, Scores, Structural Equation Models
Sijtsma, Klaas; van der Ark, L. Andries – Multivariate Behavioral Research, 2003
This article first discusses a statistical test for investigating whether or not the pattern of missing scores in a respondent-by-item data matrix is random. Since this is an asymptotic test, we investigate whether it is useful in small but realistic sample sizes. Then, we discuss two known simple imputation methods, person mean (PM) and two-way…
Descriptors: Test Items, Questionnaires, Statistical Analysis, Models

Dimitrov, Dimiter M.; Raykov, Tenko – Multivariate Behavioral Research, 2003
Presents a validation procedure for cognitive structures that is based on structural equation modeling of cognitive subordination relationships among test items. Illustrates the method using scores of 278 ninth graders on an algebra test and shows results for the same test when the linear logistic test model is used. (SLD)
Descriptors: High School Students, High Schools, Scores, Structural Equation Models

Fava, 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

Pruzek, Robert M.; Lepak, Greg M. – Multivariate Behavioral Research, 1992
Adaptive forms of weighted structural regression are developed and discussed. Bootstrapping studies indicate that the new methods have potential to recover known population regression weights and predict criterion score values routinely better than do ordinary least squares methods. The new methods are scale free and simple to compute. (SLD)
Descriptors: Equations (Mathematics), Least Squares Statistics, Mathematical Models, Predictive Measurement

Levin, Joseph – Multivariate Behavioral Research, 1986
The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Power (Statistics)

Fava, Joseph L.; Velicer, Wayne F. – Multivariate Behavioral Research, 1992
Principal component, image component, three types of factor score estimates, and one scale score method were compared over different levels of variables, saturations, sample sizes, variable to component ratios, and pattern rotations. There were virtually no overall differences among methods, with the average correlation between matched scores…
Descriptors: Comparative Analysis, Correlation, Equations (Mathematics), Estimation (Mathematics)

Zwick, Rebecca – Multivariate Behavioral Research, 1986
The purpose of the current study was to investigate the relative performance of the parametric, rank, and normal scores procedures when the classical assumptions were met and under violations of these assumptions. This investigation included the normal scores as well as the rank test. (LMO)
Descriptors: Hypothesis Testing, Mathematical Models, Measurement Techniques, Monte Carlo Methods