Bayesian tests of two proportions: A tutorial with R and JASP

Hoffmann, Tabea; Hofman, Abe D.; Wagenmakers, Eric–Jan

doi:10.5964/meth.9263

Cited by 2 publications

(2 citation statements)

References 49 publications

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“…Recent advancements in JASP have expanded its utility, particularly in terms of Bayesian analysis. Tutorials have been developed to guide users in applying Bayesian methods to specific statistical tests, such as single-test reliability analysis (Pfadt, 2022), tests of two proportions (Hoffmann et al, 2022), and Bayesian model-averaged meta-analysis (Berkhout et al, 2023). These resources are invaluable for those new to Bayesian methods, offering clear, step-by-step guidance, in a user-friendly software such as JASP.…”

Section: Statistical Analysis In Studying L2 Learning Phenomenamentioning

confidence: 99%

Exploring JASP as a data analysis tool in L2 research: a snapshot

McBride,

Garcés-Manzanera

2024

TEISEL

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This paper explores the potential of JASP (Jeffreys’s Amazing Statistics Program, https://jasp-stats.org/) as a robust statistical tool in advancing Second Language Acquisition (SLA) research, with a specific emphasis on its application within the domain of L2 writing. Second language writing proficiency is a complex and multifaceted skill, demanding rigorous empirical investigation to uncover nuanced patterns and insights. JASP, known for its user-friendly interface and advanced statistical capabilities, emerges as a promising instrument for researchers seeking to unravel the intricacies of L2 writing development. The paper begins by providing an overview of the features embedded in JASP and continues to discuss some of the extant research within the field of SLA that implements JASP as a data analysis tool. Follows is a detailed description of the use of JASP in two L2 writing papers, in which the data analysis decisions are discussed. Furthermore, the discussion delves into the practical implications of utilizing JASP in L2 writing research, including its ability to accommodate small sample sizes, handle complex interactions, and facilitate transparent and reproducible analyses. The paper concludes by advocating for the widespread adoption of JASP in SLA research, positing that its integration holds the promise of advancing our understanding of the intricacies of L2 writing development and contributing to the refinement of pedagogical approaches in second language education.

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Section: Statistical Analysis In Studying L2 Learning Phenomenamentioning

confidence: 99%

Exploring JASP as a data analysis tool in L2 research: a snapshot

McBride,

Garcés-Manzanera

2024

TEISEL

View full text Add to dashboard Cite

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“…To obtain the distribution of this difference, we can calculate the difference between posterior distributions. This difference distribution can help us answer probability questions about the difference in effects between experimental groups, such as the probability that version A is more effective than version B (Hoffmann et al, 2022).…”

Section: Ability To Handle Multiple Experimental Groupsmentioning

confidence: 99%

Incorporating media news to predict financial distress: Case study on Chinese listed companies

Zhang,

Abedin,

Liu

2024

Journal of Forecasting

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Financial distress prediction has been a prominent research field for several decades. Accurate prediction of financial distress not only helps to safeguard the interests of investors but also improves the ability of managers to manage financial risks. Prior studies predominantly rely on accounting metrics derived from financial statements to predict financial distress. Our research takes a step further by incorporating media news to enhance the accuracy of financial distress prediction. Based on the data from Chinese listed companies, seven classifiers are established to verify the additional value of media news in improving the financial distress prediction performance of models. Experimental results demonstrate that the inclusion of media news in predictive models is effective as it contributes to better performance compared with models that solely rely on accounting features. Moreover, random forest model is a reliable tool in financial distress prediction due to its superior ability to capture complex feature relationships. Evaluation indicators, statistical tests, and Bayesian A/B tests further confirm that the inclusion of media news can significantly improve the identification of financially distressed companies.

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Bayesian tests of two proportions: A tutorial with R and JASP

Cited by 2 publications

References 49 publications

Exploring JASP as a data analysis tool in L2 research: a snapshot

Exploring JASP as a data analysis tool in L2 research: a snapshot

Incorporating media news to predict financial distress: Case study on Chinese listed companies

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