NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20260
Since 20250
Since 2022 (last 5 years)0
Since 2017 (last 10 years)0
Since 2007 (last 20 years)1
Audience
Researchers1
Laws, Policies, & Programs
Elementary and Secondary…1
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 91 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Osler, James Edward; Mansaray, Mahmud A. – Journal of Educational Technology, 2013
The online deployment of Technology Engineered online Student Ratings of Instruction (SRIs) by colleges and universities in the United States has dynamically changed the deployment of course evaluation. This research investigation is the fourth part of a post hoc study that analytically and psychometrically examines the design, reliability, and…
Descriptors: Course Evaluation, Educational Technology, Black Colleges, Higher Education
SAW, J.G. – 1964
THIS VOLUME DEALS WITH THE BIVARIATE NORMAL DISTRIBUTION. THE AUTHOR MAKES A DISTINCTION BETWEEN DISTRIBUTION AND DENSITY FROM WHICH HE DEVELOPS THE CONSEQUENCES OF THIS DISTINCTION FOR HYPOTHESIS TESTING. OTHER ENTRIES IN THIS SERIES ARE ED 003 044 AND ED 003 045. (JK)
Descriptors: Hypothesis Testing, Mathematical Models, Mathematics, Statistical Analysis
Peer reviewed Peer reviewed
Borg, Ingiver; Lingoes, James C. – Psychometrika, 1980
A method for externally constraining certain distances in multidimensional scaling configurations is introduced and illustrated. The method is described in detail and several examples are presented. (Author/JKS)
Descriptors: Algorithms, Hypothesis Testing, Mathematical Models, Multidimensional Scaling
Peer reviewed Peer reviewed
Lienert, G. A.; Krauth, J. – Educational and Psychological Measurement, 1975
Configural frequency analysis (CFA), a new method for identifying types, is illustrated numerically. Relations to latent class analysis and to factor analysis are discussed. It is suggested to use CFA as a type-defining method instead of factor analysis if the variables are linked not only by first but also by higher-order associations. (RC)
Descriptors: Classification, Factor Analysis, Hypothesis Testing, Mathematical Models
Peer reviewed Peer reviewed
Games, Paul A. – American Educational Research Journal, 1978
Marascuilo's and Levin's use of the term "nesting" to describe a statistical model, and application of the Scheffe tests on restricted sets of contrasts, is opposed. Changing the model during analysis of a complex set of data is both necessary and desirable. (Author/CP)
Descriptors: Data Analysis, Factor Analysis, Hypothesis Testing, Mathematical Models
Peer reviewed Peer reviewed
Hollingsworth, Holly H. – Educational and Psychological Measurement, 1981
If the null hypothesis of a one-sample test of multivariate means is rejected, the dimension of the line joining the population centroid and the hypothesized centroid can be interpreted with a linear function, using a discriminant function and the correlation of each dependent variable with a discriminant score. (Author/BW)
Descriptors: Discriminant Analysis, Hypothesis Testing, Mathematical Models, Statistical Analysis
Peer reviewed Peer reviewed
Harwell, Michael R.; Serlin, Ronald C. – Journal of Educational Statistics, 1989
Two forms, pure-rank and mixed-rank, of a nonparametric, general, linear model-based statistic that can be used to test several hypotheses are presented. A Monte Carlo study was used to investigate the distributional properties of these forms, and their use is discussed. (SLD)
Descriptors: Hypothesis Testing, Mathematical Models, Monte Carlo Methods, Simulation
Rodger, R. S. – 1974
A fairly large number of different methods exist for evaluating comparisons or null hypothetical contrasts. Because it is difficult to choose among them, this paper develops a 2 by 2 classification of the methods. The first dimension of the classification is decision-based error rate vs. experimentwise error rate. The second dimension is planned…
Descriptors: Classification, Evaluation Methods, Hypothesis Testing, Mathematical Models
Draper, John F. – 1974
A study was made of the problem of representing the expectations of mean squares associated with analysis of variance sources of variation for experimental designs. These designs have a factorial structure over repeated measures or, for some other reason, have variates within a factorial design not all of which are mutually independent. A simple…
Descriptors: Analysis of Variance, Expectation, Hypothesis Testing, Mathematical Models
Shoemaker, David M. – 1971
Multiple matrix sampling is a psychometric procedure in which a set of test items is subdivided randomly into subtests of items with each subtest administered to different subgroups of examinees selected at random from the examinee population. Although each examinee receives only a proportion of the complete set of items, the statistical model…
Descriptors: Computer Programs, Hypothesis Testing, Item Sampling, Mathematical Models
Werts, Charles E.; And Others – 1971
To resolve a recent controversy between Klein and Cleary and Levy, a model for dichotomous congeneric items is presented which has mean errors of zero, dichotomous true scores that are uncorrelated with errors, and errors that are mutually uncorrelated. (Author)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Mathematics
Peer reviewed Peer reviewed
Bentler, P. M.; Lee, Sik-Yum – Psychometrika, 1978
A special case of Bloxom's version of Tucker's three mode factor analysis model is developed statistically. A goodness of fit test and an empirical example are presented. (Author/JKS)
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Mathematical Models
Peer reviewed Peer reviewed
Sorbom, Dag – Psychometrika, 1978
A general statistical model for simultaneous analysis of data from several groups is described. The model is primarily designed to be used for the analysis of covariance. The model can handle any number of covariates and criterion variables, and any number of treatment groups. (Author/JKS)
Descriptors: Analysis of Covariance, Hypothesis Testing, Mathematical Models, Research Design
Peer reviewed Peer reviewed
Rogan, Joanne C.; Keselman, H. J. – American Educational Research Journal, 1977
The effects of variance heterogeneity on the empirical probability of a Type I error for the analysis of variance (ANOVA) F-test are examined. The rate of Type I error varies as a function of the degree of variance heterogeneity, and the ANOVA F-test is not always robust to variance heterogeneity when sample sizes are equal. (Author/JAC)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Statistical Analysis
Peer reviewed Peer reviewed
Busk, Patricia L.; Marascuilo, Leonard A. – Australian Journal of Education, 1989
An extension of the discussion of loglinear models presents post hoc procedures for statistically evaluating treatment effects, contrasts, and confidence intervals, illustrating methods for main effect and interaction contrasts and paying special attention to odds ratios and their interval estimates. Procedures for treating variables as…
Descriptors: Estimation (Mathematics), Hypothesis Testing, Interaction, Mathematical Models
Previous Page | Next Page ยป
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7