Abstract
Historically, organizational researchers fully embraced frequentist statistics and null hypothesis significance testing (NHST). Bayesian statistics is an underused alternative paradigm offering numerous benefits for organizational researchers and practitioners: e.g., accumulating direct evidence for the null hypothesis (vs. ‘fail to reject the null’), capturing uncertainty across a distribution of population parameters (vs. a 95% confidence interval on a single point estimate) – and through these benefits, communicating statistical findings more clearly. Although I-O and other organizational methodologists in the past have promoted Bayesian methods, only now is easy-to-use JASP statistical software available for more widespread implementation. Moreover, the software is free to download and use, is menu-driven, and is supported by an active multidisciplinary user community. Using JASP, our tutorial compares and contrasts frequentist and Bayesian approaches for two analyses: a multiple linear regression analysis and a linear mixed regression analysis.
Original language | English (US) |
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Journal | Practical Assessment, Research and Evaluation |
Volume | 29 |
Issue number | 1 |
DOIs | |
State | Published - 2024 |
Keywords
- Bayesian statistics
- statistical communication
- Bayesian linear mixed model
- Bayesian regression