Analyzing the influence of binary data clustering on relative risk within the context of inferential methods-Reference-Cited by-同舟云学术

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Analyzing the influence of binary data clustering on relative risk within the context of inferential methods

Published:2024-07 Issue: Volume: Page:1-20
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Nath Gopal¹,Saha Krishna K.²,Banerjee Soumik³,Das Kumer P.⁴

Affiliation:

1. Data and Analytics, Regions Bank, Birmingham, AL, USA

2. Department of Mathematical Sciences, Central CT State University, New Britain, CT, USA

3. Department of Quantitative Sciences, Canisius University, Buffalo, NY, USA

4. The Office of Vice President for Research, Innovation, and Economic Development, University of LA at Lafayette, Lafayette, LA, USA

Funder

Simons Foundation Mathematics and Physical Sciences - Grant for Collaboration among Mathematicians

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2024.2373379

Reference29 articles.

1. Pitfalls of using the risk ratio in meta‐analysis

2. A Mixed-Effects Model for Categorical Data

3. Bishop, Y. M. M., E. F. Stephen, and H. Paul. 2007. Discrete multivariate analysis: theory and practices. New York, USA: Springer. ISBN-13: 978-0387728056

4. Tricyclic Antidepressants and Monoamine Oxidase Inhibitors: Are They Too Old for a New Look?

5. Cochran, W. G. 1977. Sampling techniques. NewYork: Wiley. ISBN 978-0-471-162407.

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