Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 2 |
Descriptor
Algorithms | 3 |
Personality Measures | 3 |
Factor Analysis | 2 |
Behavior Patterns | 1 |
Classification | 1 |
Comparative Analysis | 1 |
Construct Validity | 1 |
Extraversion Introversion | 1 |
Graphs | 1 |
Item Analysis | 1 |
Item Response Theory | 1 |
More ▼ |
Author
Daxun Wang | 1 |
Dongbo Tu | 1 |
Gongjun Xu | 1 |
Henkel, Thomas George | 1 |
Jingchen Liu | 1 |
Wilmoth, James Noel | 1 |
Xiaoou Li | 1 |
Yan Cai | 1 |
Yunxiao Chen | 1 |
Zhichen Guo | 1 |
Zhiliang Ying | 1 |
More ▼ |
Publication Type
Journal Articles | 3 |
Reports - Evaluative | 3 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
Eysenck Personality Inventory | 1 |
What Works Clearinghouse Rating
Zhichen Guo; Daxun Wang; Yan Cai; Dongbo Tu – Educational and Psychological Measurement, 2024
Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative…
Descriptors: Item Response Theory, Models, Reaction Time, Measurement Techniques
Yunxiao Chen; Xiaoou Li; Jingchen Liu; Gongjun Xu; Zhiliang Ying – Grantee Submission, 2017
Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class…
Descriptors: Item Analysis, Classification, Graphs, Test Items

Henkel, Thomas George; Wilmoth, James Noel – Journal of Experimental Education, 1992
Principal components extraction with orthogonal and oblique rotations tested the construct validity of the Personal Profile System (PPS) using data from 1,045 senior noncommissioned Air Force officers. Four factors accounted for 85 percent of the total variance, but the results do not completely justify publisher claims for the PPS. (SLD)
Descriptors: Algorithms, Behavior Patterns, Construct Validity, Factor Analysis