2021

Volume 89, n° 1, April 2021

• Ficek J, Wang W, Chen H, Dagne G, Daley E. A Survey of Differentially Private Regression for Clinical and Epidemiological Research, pp. 132-147. doi:https://doi.org/10.1111/insr.12391
• Calmon W, Ferioli E, Lettieri D, Soares J, Pizzinga A. An Extensive Comparison of Some Well-Established Value at Risk Methods, pp. 148-166. doi:https://doi.org/10.1111/insr.12393
• Yoon F. Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare, pp. 209-209. doi:https://doi.org/10.1111/insr.12440
• Stefan M, Hidiroglou M. Benchmarked Estimators for a Small Area Mean Under a Onefold Nested Regression Model, pp. 108-131. doi:https://doi.org/10.1111/insr.12380
• Utts J. Enhancing Data Science Ethics Through Statistical Education and Practice, pp. 1-17. doi:https://doi.org/10.1111/insr.12446
• Zhao L. Exploratory Subgroup Analysis in Clinical Research, pp. 209-210. doi:https://doi.org/10.1111/insr.12441
• Tutz G. Hierarchical Models for the Analysis of Likert Scales in Regression and Item Response Analysis, pp. 18-35. doi:https://doi.org/10.1111/insr.12396
• Iaco SD, Posa D, Cappello C, Maggio S. On Some Characteristics of Gaussian Covariance Functions, pp. 36-53. doi:https://doi.org/10.1111/insr.12403
• Patone M, Zhang L-C. On Two Existing Approaches to Statistical Analysis of Social Media Data, pp. 54-71. doi:https://doi.org/10.1111/insr.12404
• Hui FKC, Müller S, Welsh AH. Random Effects Misspecification Can Have Severe Consequences for Random Effects Inference in Linear Mixed Models, pp. 186-206. doi:https://doi.org/10.1111/insr.12378
• Nanda AK, Chowdhury S. Shannon’s Entropy and Its Generalisations Towards Statistical Inference in Last Seven Decades, pp. 167-185. doi:https://doi.org/10.1111/insr.12374
• Liu S. Statistical Machine Learning: A Unified Framework, pp. 210-212. doi:https://doi.org/10.1111/insr.12442
• Ghosh D. Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences, pp. 207-209. doi:https://doi.org/10.1111/insr.12439
• Williams MR, Savitsky TD. Uncertainty Estimation for Pseudo-Bayesian Inference Under Complex Sampling, pp. 72-107. doi:https://doi.org/10.1111/insr.12376

(résumés du n° 1/2021)