Descriptor
| Estimation (Mathematics) | 10 |
| Multivariate Analysis | 10 |
| Sample Size | 10 |
| Equations (Mathematics) | 4 |
| Analysis of Variance | 3 |
| Bayesian Statistics | 2 |
| Error of Measurement | 2 |
| Hypothesis Testing | 2 |
| Mathematical Models | 2 |
| Robustness (Statistics) | 2 |
| Analysis of Covariance | 1 |
| More ▼ | |
Source
| Journal of Educational… | 2 |
| Journal of Educational and… | 2 |
| Multivariate Behavioral… | 2 |
| Journal of Experimental… | 1 |
Author
Publication Type
| Journal Articles | 7 |
| Reports - Evaluative | 7 |
| Speeches/Meeting Papers | 4 |
| Reports - Research | 3 |
Education Level
Audience
| Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewedBoik, Robert J. – Journal of Educational and Behavioral Statistics, 1997
An analysis of repeated measures designs is proposed that uses an empirical Bayes estimator of the covariance matrix. The proposed analysis behaves like a univariate analysis when sample size is small or sphericity nearly satisfied, but behaves like multivariate analysis when sample size is large or sphericity is strongly violated. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Multivariate Analysis, Research Design
Peer reviewedThum, Yeow Meng – Journal of Educational and Behavioral Statistics, 1997
A class of two-stage models is developed to accommodate three common characteristics of behavioral data: (1) its multivariate nature; (2) the typical small sample size; and (3) the possibility of missing observations. The model, as illustrated, permits estimation of the full spectrum of plausible measurement error structures. (SLD)
Descriptors: Bayesian Statistics, Behavior Patterns, Estimation (Mathematics), Maximum Likelihood Statistics
Large Sample Multivariate Procedures for Comparing and Combining Effect Sizes within a Single Study.
Peer reviewedMarascuilo, Leonard A.; And Others – Journal of Experimental Education, 1988
Large sample multivariate methods for estimating and comparing effect sizes across independent samples within a single study are presented. Procedures for pooling treatment effects are provided to allow determination of overall study effect sizes for treatments with similar effects prior to implementation of meta-analyses. (TJH)
Descriptors: Effect Size, Equations (Mathematics), Estimation (Mathematics), Meta Analysis
Tucker, Mary L.; Daniel, Larry G., Jr. – 1992
The jackknife statistic is discussed as a viable invariance procedure. Data from a study of leadership illustrates the use of the jackknife in determining the stability of canonical function coefficients following canonical correlation analysis. The jackknife procedure entails arbitrarily omitting one observation or a subset of observations at a…
Descriptors: College Faculty, Correlation, Equations (Mathematics), Estimation (Mathematics)
Schmitt, Dorren Rafael – 1989
Generalizability or invariance procedures have been known for over three decades. Through the years, these procedures have not been widely discussed or employed. One reason for the lack of use is that most of the articles on invariance procedures have been mathematically oriented. The mathematical orientation of research articles and the lack of…
Descriptors: Discriminant Analysis, Educational Research, Estimation (Mathematics), Factor Analysis
Peer reviewedMacKinnon, David P.; And Others – Multivariate Behavioral Research, 1995
Analytical solutions for point and variance estimators of the mediated effect, the ratio of mediated to direct effect, and the proportion of the total effect mediated were determined through simulation for different samples. The sample sizes needed for accuracy and stability are discussed with implications for mediated effects estimates. (SLD)
Descriptors: Equations (Mathematics), Error of Measurement, Estimation (Mathematics), Multivariate Analysis
Peer reviewedBetz, M. Austin; Elliott, Steven D. – Journal of Educational Statistics, 1984
The method of unweighted means in the multivariate analysis of variance with unequal sample sizes was investigated. By approximating the distribution of the hypothesis sums-of-squares-and-cross-products with a Wishart distribution, multivariate test statistics were derived. Monte Carlo methods and a numerical example illustrate the technique.…
Descriptors: Analysis of Variance, Estimation (Mathematics), Hypothesis Testing, Multivariate Analysis
Peer reviewedKaplan, David – Multivariate Behavioral Research, 1990
A strategy for evaluating/modifying covariance structure models (CSMs) is presented. The approach uses recent developments in estimation under nonstandard conditions and unified asymptotic theory related to hypothesis testing, and it determines the extent of sample size sensitivity and specification error effects by relying on existing statistical…
Descriptors: Error of Measurement, Estimation (Mathematics), Evaluation Methods, Goodness of Fit
Elliott, Ronald S.; Barcikowski, Robert S. – 1993
This Monte Carlo study examines whether, given various numbers of variables, treatments, and sample sizes, in a one-way multivariate analysis of variance, Type I error rates of the test approximations provided by the BMDP program, the Statistical Analysis System (SAS), and the Statistical Package for the Social Sciences (SPSS) for Roy's largest…
Descriptors: Analysis of Variance, Computer Simulation, Estimation (Mathematics), Monte Carlo Methods
Peer reviewedAlgina, James; And Others – Journal of Educational Statistics, 1991
Type I error rates for Yao's, James' first-order and second-order, and Johansen's tests of equality of mean vectors for two independent samples were estimated for various conditions defined by the degree of heteroscedasticity and nonnormality. Each procedure can be seriously nonrobust with exponential and log-normal distributions. (TJH)
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Equated Scores


