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A New Approach To False Discovery Rates And Multiple Hypothesis Testing
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Book Synopsis A New Approach to False Discovery Rates and Multiple Hypothesis Testing by : John D. Storey
Download or read book A New Approach to False Discovery Rates and Multiple Hypothesis Testing written by John D. Storey and published by . This book was released on 2001 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Encyclopedia of Systems Biology by : Werner Dubitzky
Download or read book Encyclopedia of Systems Biology written by Werner Dubitzky and published by Springer. This book was released on 2013-08-17 with total page 2367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems biology refers to the quantitative analysis of the dynamic interactions among several components of a biological system and aims to understand the behavior of the system as a whole. Systems biology involves the development and application of systems theory concepts for the study of complex biological systems through iteration over mathematical modeling, computational simulation and biological experimentation. Systems biology could be viewed as a tool to increase our understanding of biological systems, to develop more directed experiments, and to allow accurate predictions. The Encyclopedia of Systems Biology is conceived as a comprehensive reference work covering all aspects of systems biology, in particular the investigation of living matter involving a tight coupling of biological experimentation, mathematical modeling and computational analysis and simulation. The main goal of the Encyclopedia is to provide a complete reference of established knowledge in systems biology – a ‘one-stop shop’ for someone seeking information on key concepts of systems biology. As a result, the Encyclopedia comprises a broad range of topics relevant in the context of systems biology. The audience targeted by the Encyclopedia includes researchers, developers, teachers, students and practitioners who are interested or working in the field of systems biology. Keeping in mind the varying needs of the potential readership, we have structured and presented the content in a way that is accessible to readers from wide range of backgrounds. In contrast to encyclopedic online resources, which often rely on the general public to author their content, a key consideration in the development of the Encyclopedia of Systems Biology was to have subject matter experts define the concepts and subjects of systems biology.
Book Synopsis A Manual of the History of Dogmas by : Bernard John Otten
Download or read book A Manual of the History of Dogmas written by Bernard John Otten and published by . This book was released on 1917 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multiple Testing and False Discovery Rate Control by : Shiyun Chen
Download or read book Multiple Testing and False Discovery Rate Control written by Shiyun Chen and published by . This book was released on 2019 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple testing, a situation where multiple hypothesis tests are performed simultaneously, is a core research topic in statistics that arises in almost every scientific field. When more hypotheses are tested, more errors are bound to occur. Controlling the false discovery rate (FDR) [BH95], which is the expected proportion of falsely rejected null hypotheses among all rejections, is an important challenge for making meaningful inferences. Throughout the dissertation, we analyze the asymptotic performance of several FDR-controlling procedures under different multiple testing settings. In Chapter 1, we study the famous Benjamini-Hochberg (BH) method [BH95] which often serves as benchmark among FDR-controlling procedures, and show that it is asymptotic optimal in a stylized setting. We then prove that a distribution-free FDR control method of Barber and Candès [FBC15], which only requires the (unknown) null distribution to be symmetric, can achieve the same asymptotic performance as the BH method, thus is also optimal. Chapter 2 proposes an interval-type procedure which identifies the longest interval with the estimated FDR under a given level and rejects the corresponding hypotheses with P-values lying inside the interval. Unlike the threshold approaches, this procedure scans over all intervals with the left point not necessary being zero. We show that this scan procedure provides strong control of the asymptotic false discovery rate. In addition, we investigate its asymptotic false non-discovery rate (FNR), deriving conditions under which it outperforms the BH procedure. In Chapter 3, we consider an online multiple testing problem where the hypotheses arrive sequentially in a stream, and investigate two procedures proposed by Javanmard and Montanari [JM15] which control FDR in an online manner. We quantify their asymptotic performance in the same location models as in Chapter 1 and compare their power with the (static) BH method. In Chapter 4, we propose a new class of powerful online testing procedures which incorporates the available contextual information, and prove that any rule in this class controls the online FDR under some standard assumptions. We also derive a practical algorithm that can make more empirical discoveries in an online fashion, compared to the state-of-the-art procedures.
Book Synopsis New Results on the False Discovery Rate by : Fang Liu
Download or read book New Results on the False Discovery Rate written by Fang Liu and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics
Book Synopsis Resampling-Based Multiple Testing by : Peter H. Westfall
Download or read book Resampling-Based Multiple Testing written by Peter H. Westfall and published by John Wiley & Sons. This book was released on 1993-01-12 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
Book Synopsis Generalized Error Control in Multiple Hypothesis Testing by : Wenge Guo
Download or read book Generalized Error Control in Multiple Hypothesis Testing written by Wenge Guo and published by . This book was released on 2007 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple hypothesis testing is concerned with appropriately controlling the rate of false positives when testing a large number of hypotheses simultaneously, while maintaining the power of each test as much as possible. For testing multiple null hypotheses, the classical approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. However, quite often, especially when a large number of hypotheses are simultaneously tested, the notion of FWER turns out to be too stringent, allowing little chance to detect many false null hypotheses. Therefore, researchers have focused in the last decade on defining alternative less stringent error rates and developing methods that control them. The false discovery rate (FDR), the expected proportion of falsely rejected null hypotheses, due to Benjamini and Hochberg (1995), is the first of these alternative error rates that has received considerable attention. Recently, the ideas of controlling the probabilities of falsely rejecting at least k null hypotheses, which is the k-FWER, and the false discovery proportion (FDP) exceeding a certain threshold y have been introduced as alternatives to the FWER and methods controlling these new error rates have been suggested. Very recently, following the idea similar to that of the k-FWER, Sarkar (2006) generalized the FDR to the k-FDR, the expected ratio of k or more false rejections to the total number of rejections, which is a less conservative notion of error rate than the FDR and k-FWER. In this work, we develop multiple testing theory and methods for controlling the new type I error rates. Specifically, it consists of four parts: (1) We develop a new stepdown FDR controlling procedure under no assumption on dependency of the underlying p-values, which has much smaller critical constants than that of the existing Benjamini-Yekutieli stepup procedure; (2) We develop new k-FWER and FDP stepdown procedures under the assumption of independence, which are much more powerful than the existing k-FWER and FDP procedures and show that under certain condition, the k-FWER stepdown procedure is unimprovable; (3) We offer a unified approach for construction of k-FWER controlling procedures by generalizing the closure principle in the context of the FWER to the case of the k-FWER; (4) We develop new Benjamini-Hochberg type k-FDR stepup and stepdown procedures in different settings and apply them to one real microarray data analysis.
Book Synopsis Large-Scale Inference by : Bradley Efron
Download or read book Large-Scale Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2012-11-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.
Book Synopsis Multiple Comparison Procedures by : Yosef Hochberg
Download or read book Multiple Comparison Procedures written by Yosef Hochberg and published by . This book was released on 1987-10-05 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in data analysis. With equal emphasis on theory and applications, it establishes the advantages of multiple comparison techniques in reducing error rates and in ensuring the validity of statistical inferences. Provides detailed descriptions of the derivation and implementation of a variety of procedures, paying particular attention to classical approaches and confidence estimation procedures. Also discusses the benefits and drawbacks of other methods. Numerous examples and tables for implementing procedures are included, making this work both practical and informative.
Book Synopsis NEW APPROACHES TO MULTIPLE TESTING OF GROUPED HYPOTHESES by : Yanping Liu
Download or read book NEW APPROACHES TO MULTIPLE TESTING OF GROUPED HYPOTHESES written by Yanping Liu and published by . This book was released on 2016 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: Testing multiple hypotheses appearing in non-overlapping groups is a common statistical problem in many modern scientific investigations, with this group formation occurring naturally in many of these investigations. The goal of this dissertation is to explore the current state of knowledge in the area of multiple testing of grouped hypotheses and to present newer and improved statistical methodologies. As the first part of this dissertation, we propose a new Bayesian two-stage multiple testing method controlling false discovery rate (FDR) across all hypotheses. The method decomposes a posterior measure of false discoveries across all hypotheses into within- and between-group components allowing a portion of the overall FDR level to be used to maintain control over within groupfalse discoveries. Such within-group FDR control effectively captures the group structure as well as the dependence, if any, within the groups. The procedure can maintain a tight control over the overall FDR,as shown numerically under two different model assumptions, independent and Markov dependent Bernoulli's, for the hidden states of the within-group hypotheses. The proposed method in its oracle form is optimal at both within-and between-group levels of its application. We also present a data driven version of the proposed method whose performance in terms of FDR control and power relative to its relevant competitors is examined through simulations. We apply this Bayesian method to a real data application, which is the Adequate Yearly Progress (AYP) study data of California elementary schools (2013) comparing the academic performance for socioeconomically advantaged (SEA) versus socioeconomically disadvantaged (SED) students, and our method has more meaningful discoveries than two other competing methods existing in the literature. The second part of the dissertation is geared towards making contribution to the outstanding problem of developing an FDR controlling frequentist method for multiple testing of grouped hypotheses, which can serve not only as an extension of the classical Benjamini -Hochberg (BH, 1995) method from single to multiple groups but also can be more powerful due to the underlying group structure. We suggest a number of such methods and examine their performances in comparison with the single-group BH method mainly based on simulations. Some possible future directions of research in the proposed area are discussed at the end of this dissertation.
Book Synopsis Recent Advances in Biostatistics by : Manish Bhattacharjee
Download or read book Recent Advances in Biostatistics written by Manish Bhattacharjee and published by World Scientific. This book was released on 2011 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume provides self-contained accounts of some recent trends in Biostatistics methodology and their applications. It includes state-of-the-art reviews and original contributions. The articles included in this volume are based on a careful sel
Book Synopsis Multiple Testing Procedures with Applications to Genomics by : Sandrine Dudoit
Download or read book Multiple Testing Procedures with Applications to Genomics written by Sandrine Dudoit and published by Springer Science & Business Media. This book was released on 2007-12-18 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. These are applied to a range of problems in biomedical and genomic research, including identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments; tests of association between gene expression measures and biological annotation metadata; sequence analysis; and genetic mapping of complex traits using single nucleotide polymorphisms. The procedures are based on a test statistics joint null distribution and provide Type I error control in testing problems involving general data generating distributions, null hypotheses, and test statistics.
Book Synopsis Multiple Testing Problems in Pharmaceutical Statistics by : Alex Dmitrienko
Download or read book Multiple Testing Problems in Pharmaceutical Statistics written by Alex Dmitrienko and published by CRC Press. This book was released on 2009-12-08 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful Statistical Approaches for Addressing Multiplicity IssuesIncludes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple c
Book Synopsis Multiple Hypothesis Testing by : Houston Nash Gilbert
Download or read book Multiple Hypothesis Testing written by Houston Nash Gilbert and published by . This book was released on 2009 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Large-scale Simultaneous Hypothesis Testing by : Bradley Efron
Download or read book Large-scale Simultaneous Hypothesis Testing written by Bradley Efron and published by . This book was released on 2003 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Testing Jumps Via False Discovery Rate Control by : Yu-Min Yen
Download or read book Testing Jumps Via False Discovery Rate Control written by Yu-Min Yen and published by . This book was released on 2019 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such situation becomes even worse when the jump occurrence is a rare event. To obtain more reliable results, we aim to control the false discovery rate (FDR), an e fficient compound error measure for erroneous rejections in multiple testing problems. We perform the test via the Barndor -Nielsen and Shephard (BNS) test statistic, and control the FDR with the Benjamini and Hochberg (BH) procedure. We provide asymptotic results for the FDR control. From simulations, we examine relevant theoretical results and demonstrate the advantages of controlling the FDR. The hybrid approach is then applied to empirical analysis on two benchmark stock indices with high frequency data.
Book Synopsis The Analysis of Gene Expression Data by : Giovanni Parmigiani
Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.