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Related papers: Methodological Issues in Multistage Genome-Wide As…

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In order to associate complex traits with genetic polymorphisms, genome-wide association studies process huge datasets involving tens of thousands of individuals genotyped for millions of polymorphisms. When handling these datasets, which…

Computational Engineering, Finance, and Science · Computer Science 2013-05-02 Elmar Peise , Diego Fabregat , Yurii Aulchenko , Paolo Bientinesi

Under two-phase designs, the outcome and several covariates and confounders are measured in the first phase, and a new predictor of interest, which may be costly to collect, can be measured on a subsample in the second phase, without…

Methodology · Statistics 2023-05-12 Jingjing Zou , Lori B. Daniels , Karen Messer , Daniel Rabinowitz

In learning-phase clinical trials in drug development, adaptive designs can be efficient and highly informative when used appropriately. In this article, we extend the multiple comparison procedures with modeling techniques (MCP-Mod)…

Methodology · Statistics 2021-08-02 Shiyang Ma , Michael P. McDermott

Two-phase sampling designs are frequently employed in epidemiological studies and large-scale health surveys. In such designs, certain variables are exclusively collected within a second-phase random subsample of the initial first-phase…

Methodology · Statistics 2024-03-25 Lingxiao Wang

The standard paradigm for the analysis of genome-wide association studies involves carrying out association tests at both typed and imputed SNPs. These methods will not be optimal for detecting the signal of association at SNPs that are not…

Two-component mixture models are particularly useful for identifying differentially expressed genes, but their performance can deteriorate markedly when the alternative distribution departs from parametric assumptions or symmetry. We…

Methodology · Statistics 2026-03-18 Sangkon Oh , Geoffrey J. McLachlan

Statistically resolving the underlying haplotype pair for a genotype measurement is an important intermediate step in gene mapping studies, and has received much attention recently. Consequently, a variety of methods for this problem have…

Machine Learning · Computer Science 2007-10-29 Matti Kääriäinen , Niels Landwehr , Sampsa Lappalainen , Taneli Mielikäinen

The graph based approach to multiple testing is an intuitive method that enables a study team to represent clearly, through a directed graph, its priorities for hierarchical testing of multiple hypotheses, and for propagating the available…

Methodology · Statistics 2025-01-07 Cyrus Mehta , Ajoy Mukhopadhyay , Martin Posch

Due to the high cost and high failure rate of Phase III trials, seamless Phase II/III designs are more and more popular to trial efficiency. A potential attraction of Phase II/III design is to allow a randomized proof-of-concept stage prior…

Applications · Statistics 2022-06-28 Guanhong Miao , Jason J. Z. Liao , Jing Yang , Keaven Anderson

Replication studies are increasingly conducted to assess the credibility of scientific findings. Most of these replication attempts target studies with a superiority design, but there is a lack of methodology regarding the analysis of…

Methodology · Statistics 2024-12-13 Charlotte Micheloud , Leonhard Held

In many scenarios such as genome-wide association studies where dependences between variables commonly exist, it is often of interest to infer the interaction effects in the model. However, testing pairwise interactions among millions of…

Methodology · Statistics 2022-09-02 Jingyi Duan , Yang Ning , Xi Chen , Yong Chen

This paper studies inference in two-stage randomized experiments under covariate-adaptive randomization. In the initial stage of this experimental design, clusters (e.g., households, schools, or graph partitions) are stratified and randomly…

Econometrics · Economics 2026-01-16 Jizhou Liu

Predicting the cheapest sample size for the optimal stratification in multivariate survey design is a problem in cases where the population frame is large. A solution exists that iteratively searches for the minimum sample size necessary to…

Methodology · Statistics 2018-06-18 Mervyn O'Luing , Steven Prestwich , S. Armagan Tarim

Estimating causal effects under interference is pertinent to many real-world settings. Recent work with low-order potential outcomes models uses a rollout design to obtain unbiased estimators that require no interference network…

Methodology · Statistics 2025-02-12 Mayleen Cortez-Rodriguez , Matthew Eichhorn , Christina Lee Yu

Taking advantages of high-throughput genotyping technology of single nucleotide polymorphism (SNP), large genome-wide association studies (GWASs) have been considered as the promise to unravel the complex relationships between genotypes and…

Genomics · Quantitative Biology 2018-11-20 Xuan Guo

Two-stage randomization is a powerful design for estimating treatment effects in the presence of interference; that is, when one individual's treatment assignment affects another individual's outcomes. Our motivating example is a two-stage…

Applications · Statistics 2017-05-02 Guillaume Basse , Avi Feller

The traditional more-is-better dose selection paradigm, developed based on cytotoxic chemotherapeutics, is often problematic When applied to the development of novel molecularly targeted agents (e.g., kinase inhibitors, monoclonal…

Methodology · Statistics 2022-11-04 Liyun Jiang , Ying Yuan

Survey researchers are increasingly turning to multimode data collection to deal with declines in survey response rates and increasing costs. An efficient approach offers the less costly modes (e.g., web) followed with a more expensive mode…

Methodology · Statistics 2023-03-24 J. Michael Brick , Jill M. DeMatteis

Purpose: Two-stage single-arm trial designs are commonly used in phase II oncology to infer treatment effects for a binary primary outcome (e.g., tumour response). It is imperative that such studies be designed, analysed, and reported…

Applications · Statistics 2020-07-09 Michael J. Grayling , Adrian P. Mander

It is imperative for testing to determine if the components within large-scale software systems operate functionally. Interaction testing involves designing a suite of tests, which guarantees to detect a fault if one exists among a small…

Neural and Evolutionary Computing · Computer Science 2020-02-14 Ryan E. Dougherty