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) | 1 |
Descriptor
| Item Analysis | 2 |
| Test Items | 2 |
| Attitude Measures | 1 |
| Cluster Analysis | 1 |
| Factor Analysis | 1 |
| Goodness of Fit | 1 |
| Item Response Theory | 1 |
| Measures (Individuals) | 1 |
| Methods | 1 |
| Personality Measures | 1 |
| Rating Scales | 1 |
| More ▼ | |
Source
| Multivariate Behavioral… | 2 |
Publication Type
| Journal Articles | 2 |
| Reports - Descriptive | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Direct linkPolak, Marike; De Rooij, Mark; Heiser, Willem J. – Multivariate Behavioral Research, 2012
In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…
Descriptors: Item Response Theory, Measures (Individuals), Test Items, Item Analysis
Peer reviewedRevelle, William – Multivariate Behavioral Research, 1979
Hierarchical cluster analysis is shown to be an effective method for forming scales from sets of items. Comparisons with factor analytic techniques suggest that hierarchical analysis is superior in some respects for scale construction. (Author/JKS)
Descriptors: Cluster Analysis, Factor Analysis, Item Analysis, Rating Scales
