Descriptor
Source
| Evaluation Review | 2 |
| Multivariate Behavioral… | 2 |
| Educational and Psychological… | 1 |
| New Directions for Program… | 1 |
Author
| Dwyer, James H. | 1 |
| Guttman, Louis | 1 |
| Hedges, Larry V. | 1 |
| Howell, David C. | 1 |
| McConaughy, Stephanie H. | 1 |
| Rhodes, William M. | 1 |
| Roskam, Edward E. | 1 |
| Scheuneman, Janice Dowd | 1 |
| Sheldon, M. Stephen | 1 |
Publication Type
| Opinion Papers | 8 |
| Journal Articles | 6 |
| Reports - Research | 3 |
| Information Analyses | 2 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewedHowell, David C.; McConaughy, Stephanie H. – Educational and Psychological Measurement, 1982
It is argued here that the choice of the appropriate method for calculating least squares analysis of variance with unequal sample sizes depends upon the question the experimenter wants to answer about the data. The different questions reflect different null hypotheses. An example is presented using two alternative methods. (Author/BW)
Descriptors: Analysis of Variance, Hypothesis Testing, Least Squares Statistics, Mathematical Models
Peer reviewedHedges, Larry V. – New Directions for Program Evaluation, 1984
The adequacy of traditional effect size measures for research synthesis is challenged. Analogues to analysis of variance and multiple regression analysis for effect sizes are presented. The importance of tests for the consistency of effect sizes in interpreting results, and problems in obtaining well-specified models for meta-analysis are…
Descriptors: Analysis of Variance, Effect Size, Mathematical Models, Meta Analysis
Peer reviewedRoskam, Edward E.; And Others – Multivariate Behavioral Research, 1992
First- and second-round commentaries on an article by L. Guttman are presented. The following authors responded, with two articles each: (1) E. E. Roskam and J. Ellis; (2) P. H. Schonemann; (3) A. R. Jensen; (4) J. C. Loehlin; and (5) J.-E. Gustafsson. (SLD)
Descriptors: Factor Analysis, Groups, Intelligence, Mathematical Models
Peer reviewedRhodes, William M. – Evaluation Review, 1985
Prediction of success in a special program often guides program participant selection and treatment. If the statistical analysis used to develop such predictions is based on the special selectivity built into the program, the predictions can be misleading and the validation tests uninformative. Federal district court pretrial release data is used…
Descriptors: Cohort Analysis, Criminals, Mathematical Models, Predictive Validity
Sheldon, M. Stephen – 1981
Several models for enrollment projections have been developed based on past performance. One of these, a computer-assisted model developed at the California State University at Northridge, was tested for possible use at Los Angeles Pierce College (LAPC). From three to five previous comparable college terms are used in the model to predict…
Descriptors: Community Colleges, Enrollment Projections, Enrollment Trends, Mathematical Models
Peer reviewedGuttman, Louis – Multivariate Behavioral Research, 1992
Argues that Jensen's article contains an inaccurate and misleading account of Spearman's work and distorts the basic concepts of factor analysis. The target article has failed in all its main objectives; its major failing is a result of the irrelevance of factor analysis to the study of group differences. (SLD)
Descriptors: Blacks, Equations (Mathematics), Factor Analysis, Groups
Scheuneman, Janice Dowd – 1990
The current status of item response theory (IRT) is discussed. Several IRT methods exist for assessing whether an item is biased. Focus is on methods proposed by L. M. Rudner (1975), F. M. Lord (1977), D. Thissen et al. (1988) and R. L. Linn and D. Harnisch (1981). Rudner suggested a measure of the area lying between the two item characteristic…
Descriptors: Chi Square, Error of Measurement, Estimation (Mathematics), Goodness of Fit
Peer reviewedDwyer, James H. – Evaluation Review, 1984
A solution to the problem of specification error due to excluded variables in statistical models of treatment effects in nonrandomized (nonequivalent) control group designs is presented. It involves longitudinal observation with at least two pretests. A maximum likelihood estimation program such as LISREL may provide reasonable estimates of…
Descriptors: Control Groups, Mathematical Models, Maximum Likelihood Statistics, Monte Carlo Methods


