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Testing complex models with small sample sizes: A historical overview and empirical demonstration of what Partial Least Squares (PLS) can offer differential psychology
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“Additionally, when models contain a large number of constructs and items, PLS-SEM offers solutions for small sample sizes (Fornell and Larcker, 1981; Willaby et al., 2015; Hair et al., 2017b).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Willaby et al., 2015
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Metadata
- Authors
- Willaby, H. W., Costa, D. S. J., Burns, B. D., MacCann, C., & Roberts, R. D.
- Affiliations
- The University of Sydney (AU)
- Professional Examination Service (US)
- Corresponding author
- Willaby, Harold W.
- Venue
- Personality and Individual Differences
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 84
- Pages
- 73-78
- ISSN
- 0191-8869 (ISSN-L)
- OpenAlex
- W1985977391
- Cited by
- 419
- References
- 24
- Citations by year
- 2026: 37 · 2025: 68 · 2024: 60 · 2023: 53 · 2022: 50 · 2021: 58 · 2020: 34 · 2019: 14 · 2018: 18 · 2017: 12 · 2016: 11 · 2015: 3
- FWCI
- 11.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Personality and Individual Differences (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Keywords
- partial least squares path modeling, structural equation modeling, small sample size, differential psychology, mediation model, formative constructs, model fit, complex models, sample size requirements
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