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High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a…

Methodology · Statistics 2017-07-11 James Liley

Efficient two-stage group testing algorithms that are particularly suited for rapid and less-expensive DNA library screening and other large scale biological group testing efforts are investigated in this paper. The main focus is on novel…

Data Structures and Algorithms · Computer Science 2018-07-03 Michael Huber

Two-phase design can reduce the cost of epidemiological studies by limiting the ascertainment of expensive covariates or/and exposures to an efficiently selected subset (phase-II) of a larger (phase-I) study. Efficient analysis of the…

Methodology · Statistics 2019-11-04 Prosenjit Kundu , Nilanjan Chatterjee

In a high dimensional regression setting in which the number of variables ($p$) is much larger than the sample size ($n$), the number of possible two-way interactions between the variables is immense. If the number of variables is in the…

Methodology · Statistics 2024-06-26 Marianne A Jonker , Luc van Schijndel , Eric Cator

The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected subsample. It is natural to apply such a strategy for collecting genetic data in a subsample enriched for exposure…

Applications · Statistics 2013-05-27 Jaeil Ahn , Bhramar Mukherjee , Stephen B. Gruber , Malay Ghosh

Data collection costs can vary widely across variables in data science tasks. Two-phase designs can be employed to save data collection costs. This paper considers the two-phase studies where inexpensive variables are collected for all…

Methodology · Statistics 2025-12-04 Ruoyu Wang , Qihua Wang , Wang Miao

The paramount importance of replicating associations is well recognized in the genome-wide associaton (GWA) research community, yet methods for assessing replicability of associations are scarce. Published GWA studies often combine…

Methodology · Statistics 2014-04-30 Ruth Heller , Daniel Yekutieli

High-dimensional phenotypes hold promise for richer findings in association studies, but testing of several phenotype traits aggravates the grand challenge of association studies, that of multiple testing. Several methods have recently been…

Methodology · Statistics 2013-05-14 Pekka Marttinen , Jussi Gillberg , Aki Havulinna , Jukka Corander , Samuel Kaski

A computationally simple genome-wide association study (GWAS) algorithm for estimating the main and epistatic effects of markers or single nucleotide polymorphisms (SNPs) is proposed. It is based on the intuitive assumption that changes of…

Quantitative Methods · Quantitative Biology 2017-08-08 Lev V. Utkin , Irina L. Utkina

Two-phase methods are commonly used to solve bi-objective combinatorial optimization problems. In the first phase, all extreme supported nondominated points are generated through a dichotomic search. This phase also allows the…

Data Structures and Algorithms · Computer Science 2025-04-10 Felipe O. Mota , Luís Paquete , Daniel Vanderpooten

This paper studies a two-stage model of experimentation, where the researcher first samples representative units from an eligible pool, then assigns each sampled unit to treatment or control. To implement balanced sampling and assignment,…

Econometrics · Economics 2023-08-22 Max Cytrynbaum

The use of drug combinations in clinical trials is increasingly common during the last years since a more favorable therapeutic response may be obtained by combining drugs. In phase I clinical trials, most of the existing methodology…

Methodology · Statistics 2020-02-17 José L. Jiménez , Sungjin Kim , Mourad Tighiouart

Replication helps ensure that a genotype-phenotype association observed in a genome-wide association (GWA) study represents a credible association and is not a chance finding or an artifact due to uncontrolled biases. We discuss…

Methodology · Statistics 2010-10-26 Peter Kraft , Eleftheria Zeggini , John P. A. Ioannidis

Two-phase sampling is commonly adopted for reducing cost and improving estimation efficiency. In many two-phase studies, the outcome and some cheap covariates are observed for a large sample in Phase I, and expensive covariates are obtained…

Methodology · Statistics 2025-10-14 Qingning Zhou , Kin Yau Wong

Adaptive designs have been proposed for clinical trials in which the nuisance parameters or alternative of interest are unknown or likely to be misspecified before the trial. Whereas most previous works on adaptive designs and mid-course…

Methodology · Statistics 2011-05-18 Jay Bartroff , Tze Leung Lai

For the vast majority of genome wide association studies (GWAS) published so far, statistical analysis was performed by testing markers individually. In this article we present some elementary statistical considerations which clearly show…

Applications · Statistics 2010-10-04 Florian Frommlet , Felix Ruhaltinger , Piotr Twarog , Malgorzata Bogdan

We tackle the problem of quantifying failure probabilities for expensive deterministic computer experiments with stochastic inputs under a fixed budget. The computational cost of the computer simulation prohibits direct Monte Carlo (MC) and…

Methodology · Statistics 2025-07-08 Annie S. Booth , S. Ashwin Renganathan

Genome-wide association studies (GWAS) have identified hundreds of loci at very stringent levels of statistical significance across many different human traits. However, it is now clear that very large samples (n~10^4-10^5) are needed to…

Genomics · Quantitative Biology 2013-08-20 Inti Pedroso

We propose a resampling-based fast variable selection technique for detecting relevant single nucleotide polymorphisms (SNP) in a multi-marker mixed effect model. Due to computational complexity, current practice primarily involves testing…

Applications · Statistics 2025-04-30 Subhabrata Majumdar , Saonli Basu , Matt McGue , Snigdhansu Chatterjee

In the first stage of a two-stage study, the researcher uses a statistical model to impute the unobserved exposures. In the second stage, imputed exposures serve as covariates in epidemiological models. Imputation error in the first stage…

Applications · Statistics 2021-07-19 Ron Sarafian , Itai Kloog , Jonathan D. Rosenblatt
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