An Index of Factorial Simplicity
Abstract
An index of factorial simplicity, employing the quartimax transformational criteria of Carroll, Wrigley and Neuhaus, and Saunders, is developed. This index is both for each row separately and for a factor pattern matrix as a whole. The index varies between zero and one. The problem of calibrating the index is discussed.
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The observed components met Kaiser-Meyer-Olkin's (KMO) benchmark and the eigen-values of greater than one.
“Further, the observed components met Kaiser-Meyer-Olkin's (KMO) benchmark (Kaiser, 1974) and the eigen-values of greater than one.”
From Using T-O-E theoretical framework to study the adoption of ERP solution (2016) · cites this paper as Kaiser, 1974
PCA was considered feasible if the KMO measure was greater than 0.6 and the Bartlett's test of sphericity p-value was less than 0.05.
“PCA was considered feasible if the KMO measure was greater than 0.6 and the Bartlett's test of sphericity p-value was less than 0.05 [41][42][43][44].”
From Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic (2024) · cites this paper as [41]
The sampling adequacy can be accepted with a middling value of KMO = 0.794.
“Results revealed that the sampling adequacy can be accepted with a middling value of KMO = 0.794 (Kaiser, 1974) indicating low partial correlations between variables.”
From Development and Validation of a Theory-Based Questionnaire to Measure Different Types of Cognitive Load (2023) · cites this paper as Kaiser, 1974
The item reduction increased the KMO to 0.835.
“The item reduction increased the KMO to 0.835 which can be interpreted as a meritorious value (Kaiser, 1974).”
From Development and Validation of a Theory-Based Questionnaire to Measure Different Types of Cognitive Load (2023) · cites this paper as Kaiser, 1974
For the remaining 31 items in Study 1, the Kaiser-Meyer-Olkin test of sampling adequacy was .933, indicating a good degree of non-unique covariance.
“For the remaining 31 items, the Keiser-Meier-Olkin test of sampling adequacy (KMO) was .933, which indicates a good degree of non-unique covariance amongst the set of items”
From The development and initial validation of the cognitive fusion questionnaire (2014) · cites this paper as Kaiser, 1974
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AN ANALYTIC METHOD FOR ROTATION TO ORTHOGONAL SIMPLE STRUCTURE
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- Authors
- Kaiser, H. F.
- Affiliations
- United States Coast Guard Academy (US)
- Corresponding author
- Kaiser, Henry F.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1974-03
- Volume
- 39
- Issue
- 1
- Pages
- 31-36
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W1993760488
- Cited by
- 14,898
- References
- 4
- Citations by year
- 2026: 1557 · 2025: 1420 · 2024: 1148 · 2023: 1059 · 2022: 1044 · 2021: 1171 · 2020: 892 · 2019: 842 · 2018: 700 · 2017: 622 · 2016: 584 · 2015: 574 · 2014: 582 · 2013: 513 · 2012: 421
- FWCI
- 6.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychometrika (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Keywords
- index development, index calibration, factor analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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