Stats & Data Science Views has published a number of Layman’s Abstracts for articles recently published in Statistics in Medicine. The aim is to highlight the latest research to a broader audience in an accessible format. Read this collection of abstracts published since August 2020.
- , . A prediction‐based test for multiple endpoints. Statistics in Medicine. 2020; 39: 4267– 4280. https://doi.org/10.1002/sim.8724 Layman’s Abstract Open Access
- , . Direct estimation of the area under the receiver operating characteristic curve with verification biased data. Statistics in Medicine. 2020; 4789-4820. https://doi.org/10.1002/sim.8753 Layman’s Abstract
- , , , , . Formulating causal questions and principled statistical answers. Statistics in Medicine. 2020; 4922-4948. https://doi.org/10.1002/sim.8741 Layman’s Abstract Tutorial in Biostatistics Open Access
- , , , . Classification algorithm for high‐dimensional protein markers in time‐course data. Statistics in Medicine. 2020; 4201-4217. https://doi.org/10.1002/sim.8720 Layman’s Abstract
- , . Meta‐analysis of quantile intervals from different studies with an application to a pulmonary tuberculosis data. Statistics in Medicine. 2020; 4519-4537. https://doi.org/10.1002/sim.8738 Layman’s Abstract
- , . Regression with a right‐censored predictor using inverse probability weighting methods. Statistics in Medicine. 2020; 4001-4015. https://doi.org/10.1002/sim.8704 Layman’s Abstract
- , , , . Bayesian methods for the analysis of early‐phase oncology basket trials with information borrowing across cancer types. Statistics in Medicine. 2020; 39: 3459–3475. https://doi.org/10.1002/sim.8675 Layman’s Abstract
- Hoogland, J, van Barreveld, M, Debray, TPA, et al. Handling missing predictor values when validating and applying a prediction model to new patients. Statistics in Medicine. 2020; 3591-3607. https://doi.org/10.1002/sim.8682 Layman’s Abstract Open Access
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