Article
Medicine, Research & Experimental
Hong-Wei Cai, Xun Zhou
Summary: PBD is widely used in clinical trials due to its simplicity, but may lead to selection bias. BSD, theoretically superior, faces practical challenges in stratified randomization regarding imbalance, reproducibility, and bias. Solutions proposed and tested through simulations.
CONTEMPORARY CLINICAL TRIALS
(2021)
Article
Multidisciplinary Sciences
Xianghong Hu, Jia Zhao, Zhixiang Lin, Yang Wang, Heng Peng, Hongyu Zhao, Xiang Wan, Can Yang
Summary: Mendelian randomization (MR) is a valuable tool for inferring causal relationships among traits using summary statistics from GWASs, but existing methods often rely on strong assumptions leading to false-positive findings. Research has shown that considering pleiotropy and sample structure is crucial for reducing confounding effects.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Statistics & Probability
Victoria P. Johnson
Summary: This paper introduces a new randomization procedure by conditioning Efron's biased coin design to a prespecified final balance, which guarantees final balance as opposed to the original biased coin. As the sample size increases, the new design shows similarities with the original biased coin in terms of selection bias and intermediate balance. The new procedure demonstrates that by conditioning an existing randomization procedure to a subset in its allocation space, new relationships among existing designs can be established, highlighting the versatile nature of randomization.
ELECTRONIC JOURNAL OF STATISTICS
(2021)
Article
Genetics & Heredity
Zhao Yang, C. Mary Schooling, Man Ki Kwok
Summary: The study highlights the importance of selection bias in Mendelian randomization studies, proposing the use of control exposures to validate estimated causal effects. It demonstrates the potential impact of selection bias on genetic instrument-outcome associations, leading to distorted Mendelian randomization estimates.
FRONTIERS IN GENETICS
(2021)
Article
Mathematical & Computational Biology
Arvid Sjolander, Thomas Frisell, Sara Oberg, Yunzhang Wang, Sara Hagg
Summary: This article explores the combination of Mendelian randomization (MR) and sibling comparison design, discussing the feasibility and bias issues, and provides theoretical results and conclusions based on real data.
STATISTICS IN MEDICINE
(2023)
Article
Public, Environmental & Occupational Health
Qian Yang, Eleanor Sanderson, Kate Tilling, Maria Carolina Borges, Deborah A. Lawlor
Summary: With the increasing size and number of genome-wide association studies, it is increasingly found that single nucleotide polymorphisms are associated with multiple traits. Different mechanisms can lead to these associations and bias causal research results. The study uses causal diagrams to illustrate various scenarios that can result in associations between candidate instruments and non-exposure traits, and proposes measures to explore mechanisms and mitigate bias in causal estimation.
EUROPEAN JOURNAL OF EPIDEMIOLOGY
(2022)
Article
Political Science
Molly Offer-Westort, Alexander Coppock, Donald P. Green
Summary: Researchers using adaptive designs with dynamic allocation can discover the most effective treatment arm more quickly and improve the precision of their effect estimates.
AMERICAN JOURNAL OF POLITICAL SCIENCE
(2021)
Article
Biology
Matthew J. Tudball, Rachael A. Hughes, Kate Tilling, Jack Bowden, Qingyuan Zhao
Summary: Many partial identification problems can be addressed by deriving asymptotically valid confidence intervals for the optimal value. We applied this method to the problem of selection bias and showed that incorporating population-level auxiliary information can lead to more informative results. Simulation studies and a motivating example further support the development and application of our method.
Article
Genetics & Heredity
C. M. Schooling, P. M. Lopez, Z. Yang, J. V. Zhao, Shiu Lun Au Yeung, Jian V. Huang
Summary: Mendelian randomization studies face challenges in addressing selection bias, but adjusting for common causes of survival and outcome can help improve bias. Multivariable MR estimates for the effect of statins on stroke yielded different conclusions after controlling for major causes of survival and stroke.
FRONTIERS IN GENETICS
(2021)
Article
Mathematical & Computational Biology
Olga M. Kuznetsova
Summary: In a randomized open-label single-center trial, the investigator's knowledge of treatment assignments can introduce selection bias. The truncated binomial design and the big stick design were shown to minimize selection bias in different scenarios. This article suggests controlling both treatment balance and selection bias through the big stick randomization within an acceptable allocation space, which may increase with time, especially when the investigator is not aware of the allocation procedure.
STATISTICS IN BIOPHARMACEUTICAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Pan Gao, Mingqiang Wei
Summary: In geometry-based point cloud compression, the size of the blocks in the voxelized point clouds, determined by octree coding, affects whether the geometry coding is lossless or lossy. An optimal block size selection scheme is crucial for compression quality. The proposed algorithm analyzes gradients in quality and selects octree levels for point cloud compression to achieve the best results.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Civil
F. P. Bakker, N. De Koker, C. Viljoen
Summary: This study aims to solve the challenge of spatial variation in wind climate for wind power design by framing it as a model selection and bias variance trade-off problem. By incorporating both site statistics and regionally averaged statistics through the use of characteristic wind speed, an optimal estimator of design wind speed is developed. This estimator varies based on the available data quantity at a specific site and its correspondence to the regional average.
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
(2022)
Article
Mathematics, Applied
Abd El-Raheem M. Abd El-Raheem, Mona Hosny
Summary: In this article, the saddlepoint approximation method is used to approximate the exact p-value of nonparametric tests for current status and panel count data under a generalized permuted block design. The simulation study confirms that the saddlepoint approximation method is more accurate and powerful than existing approximation methods. Real data sets are also analyzed and displayed as illustrative examples.
Article
Medicine, Research & Experimental
Erin Leister Chaussee, L. Miriam Dickinson, Diane L. Fairclough
Summary: The study proposes a covariate-constrained randomization method for use in stepped wedge designs, comparing treatment effect estimation, type I error, and power under various design and confounding settings through simulation study. Optimal statistical properties were observed when potential randomizations with high imbalance were excluded using the balance metric, and when analysis methods were adjusted for potential confounders.
CONTEMPORARY CLINICAL TRIALS
(2021)
Article
Mathematics, Interdisciplinary Applications
Mattias Nordin, Marten Schultzberg
Summary: This article explores the risks and solutions of using heavily restricted randomization designs in randomized controlled trials, proposing a novel combinatoric-based approach. By validating known properties, introducing a new diagnostic measure, and demonstrating the linear relationship between MSE variance and the diagnostic measure, the study provides insights on detecting and mitigating the high MSE risk in restricted designs.
JOURNAL OF CAUSAL INFERENCE
(2022)
