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) | 2 |
Descriptor
Computer Software | 4 |
Factor Analysis | 4 |
Simulation | 3 |
Mathematical Models | 2 |
Matrices | 2 |
Algorithms | 1 |
Change | 1 |
Comparative Analysis | 1 |
Componential Analysis | 1 |
Correlation | 1 |
Data | 1 |
More ▼ |
Source
Multivariate Behavioral… | 4 |
Publication Type
Journal Articles | 4 |
Reports - Research | 2 |
Reports - Descriptive | 1 |
Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Ferrari, Pier Alda; Barbiero, Alessandro – Multivariate Behavioral Research, 2012
The increasing use of ordinal variables in different fields has led to the introduction of new statistical methods for their analysis. The performance of these methods needs to be investigated under a number of experimental conditions. Procedures to simulate from ordinal variables are then required. In this article, we deal with simulation from…
Descriptors: Data, Statistical Analysis, Sampling, Simulation
Dinno, Alexis – Multivariate Behavioral Research, 2009
Horn's parallel analysis (PA) is the method of consensus in the literature on empirical methods for deciding how many components/factors to retain. Different authors have proposed various implementations of PA. Horn's seminal 1965 article, a 1996 article by Thompson and Daniel, and a 2004 article by Hayton, Allen, and Scarpello all make assertions…
Descriptors: Structural Equation Models, Item Response Theory, Computer Software, Surveys

Wood, Phillip – Multivariate Behavioral Research, 1992
Two Statistical Analysis System (SAS) macros are presented that perform the modified principal components approach of L. R. Tucker (1966) to modeling generalized learning curves analysis up to a rotation of the components. Three SAS macros are described that rotate the factor patterns to have characteristics Tucker considered desirable. (SLD)
Descriptors: Algorithms, Change, Computer Software, Factor Analysis

Collins, Linda M.; And Others – Multivariate Behavioral Research, 1986
The present study compares the performance of phi coefficients and tetrachorics along two dimensions of factor recovery in binary data. These dimensions are (1) accuracy of nontrivial factor identifications; and (2) factor structure recovery given a priori knowledge of the correct number of factors to rotate. (Author/LMO)
Descriptors: Computer Software, Factor Analysis, Factor Structure, Item Analysis