Understanding Alpha and Beta and Sources of Common Variance
Theoretical Underpinnings and a Practical Example
Bibliographic Data
| ID | 21352154 |
|---|---|
| Authors | Steven P Reise (0000-0002-5408-6992, Department of Psychology, University of California, Los Angeles, corresponding author), Mark G Haviland (0009-0002-2642-1586, Department of Psychiatry, Loma Linda (CA) University School of Medicine) |
| Year | 2025 |
| Volume | 107 |
| Issue | 3 |
| Pages | 267-282 |
| Publication date | 2025-05-04 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Personality Assessment (JOURNAL) |
| Journal identifiers | ISSN: 0022-3891 • E-ISSN: 1532-7752 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00223891.2024.2420175 |
| PMID | 39509539 |
| OpenAlex | W4404134229 |
| Language | EN |
| Citations received | 1 |
| References cited | 46 |
Coefficient alpha estimates the degree to which scale scores reflect systematic variation due to one or more common dimensions. Coefficient beta, on the other hand, estimates the degree to which scale scores reflect a single dimension common among all the items; that is, the target construct a scale attempts to measure. As such, the magnitude of beta, relative to alpha, informs on the ability to meaningfully interpret derived scale scores as reflecting a single construct. Despite its clear interpretative usefulness, coefficient beta is rarely reported and, perhaps, not well understood. As such, we first describe how coefficient alpha and beta are analogues to model-based reliability coefficients omega total and omega hierarchical. We then demonstrate with simulated data how these indices function under a variety of data structures. Finally, we perform a hierarchical cluster analysis of the Multidimensional Personality Questionnaire's Stress Reaction Scale, estimating alpha and beta, as clusters form. This demonstrates a chief advantage of alpha and beta; they do not require a formal structural model. Moreover, we illustrate how scales that primarily are based on sets of homogeneous item clusters can "ramp up" to yield reliable scores with conceptual breadth and predominantly reflect the intended target construct
Alpha (finance) · BETA (programming language) · Cartography · Construct (python library) · Construct validity · Cronbach's alpha · Developmental psychology · Dimension (graph theory) · Explained variation · Function (biology) · Geography · Multilevel model · Physics · Psychometrics · Reliability (semiconductor) · Scale (ratio) · Statistics · Variance (accounting) · Behavioral Health and Interventions · Computer Science · Mathematics · Mental Health Research Topics · Psychology · Psychometric Methodologies and Testing
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Cronbach’s α , Revelle’s β , and Mcdonald’s ω H
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On the Dimensional and Hierarchical Structure of Affect
Thanks coefficient alpha, we’ll take it from here.
What is coefficient alpha? An examination of theory and applications.
Construct Validation in Social and Personality Research
Congeneric and (Essentially) Tau-Equivalent Estimates of Score Reliability
The Importance of Factor-Trueness and Validity, Versus Homogeneity and Orthogonality, in Test Scales1
On the Added Value of Multiple Factor Score Estimates in Essentially Unidimensional Models
Multidimensionality and Structural Coefficient Bias in Structural Equation Modeling
Hierarchical Cluster Analysis And The Internal Structure Of Tests
Exploratory Bifactor Analysis
Functionally Unidimensional Item Response Models for Multivariate Binary Data
The construction of unidimensional tests
Coefficient alpha and the internal structure of tests
Computerized adaptive personality assessment
Gender differences on negative affectivity
Construct validity
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |