Descriptor
| Item Sampling | 3 |
| Mathematical Models | 3 |
| Tables (Data) | 3 |
| Statistical Analysis | 2 |
| Test Construction | 2 |
| Analysis of Variance | 1 |
| Data Collection | 1 |
| Factor Analysis | 1 |
| Goodness of Fit | 1 |
| Group Norms | 1 |
| Individual Testing | 1 |
| More ▼ | |
Publication Type
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewedBarcikowski, Robert S. – Journal of Educational Measurement, 1972
These results indicate that in deciding on the data-gathering design to be used in seeking norm information, attention should be given to item characteristics and test length with particular attention paid to the range of biserial correlations between item response and ability. (Author)
Descriptors: Item Sampling, Mathematical Models, Measurement Techniques, Monte Carlo Methods
Peer reviewedBunda, Mary Anne – Journal of Educational Measurement, 1973
Procedures to be applicable in situations in which large numbers of individuals are tested or in situations where multiple measures are taken. (Author/CB)
Descriptors: Data Collection, Group Norms, Individual Testing, Item Sampling
Peer reviewedTucker, Ledyard R.; Lewis, Charles – Psychometrika, 1973
Maximum likelihood factor analysis provides an effective method for estimation of factor matrices and a useful test statistic in the likelihood ratio for rejection of overly simple factor models. A reliability coefficient is proposed for analysis of factor solution. (Author/RK)
Descriptors: Analysis of Variance, Factor Analysis, Goodness of Fit, Item Sampling
