Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Some New Developments On Multiple Testing Procedures
Download Some New Developments On Multiple Testing Procedures full books in PDF, epub, and Kindle. Read online Some New Developments On Multiple Testing Procedures ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Some New Developments on Multiple Testing Procedures by : Lilun Du
Download or read book Some New Developments on Multiple Testing Procedures written by Lilun Du and published by . This book was released on 2015 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the context of large-scale multiple testing, hypotheses are often accompanied with certain prior information. In chapter 2, we present a single-index modulated multiple testing procedure, which maintains control of the false discovery rate while incorporating prior information, by assuming the availability of a bivariate p-value for each hypothesis. To find the optimal rejection region for the bivariate p-value, we propose a criteria based on the ratio of probability density functions of the bivariate p-value under the true null and non-null. This criteria in the bivariate normal setting further motivates us to project the bivariate p-value to a single index p-value, for a wide range of directions. The true null distribution of the single index p-value is estimated via parametric and nonparametric approaches, leading to two procedures for estimating and controlling the false discovery rate. To derive the optimal projection direction, we propose a new approach based on power comparison, which is further shown to be consistent under some mild conditions. Multiple testing based on chi-squared test statistics is commonly used in many scientific fields such as genomics research and brain imaging studies. However, the challenges associated with designing a formal testing procedure when there exists a general dependence structure across the chi-squared test statistics have not been well addressed. In chapter 3, we propose a Factor Connected procedure to fill in this gap. We first adopt a latent factor structure to construct a testing framework for approximating the false discovery proportion (FDP) for a large number of highly correlated chi-squared test statistics with finite degrees of freedom k. The testing framework is then connected to simultaneously testing k linear constraints in a large dimensional linear factor model involved with some observable and unobservable common factors, resulting in a consistent estimator of FDP based on the associated unadjusted p-values.
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 Recent Developments in Multiple Comparison Procedures by : Yoav Benjamini
Download or read book Recent Developments in Multiple Comparison Procedures written by Yoav Benjamini and published by IMS. This book was released on 2004 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis New Developments in Multiple Testing and Multivariate Testing for High-dimensional Data by : Zongliang Hu
Download or read book New Developments in Multiple Testing and Multivariate Testing for High-dimensional Data written by Zongliang Hu and published by . This book was released on 2018 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis aims to develop some new and novel methods in advancing multivariate testing and multiple testing for high-dimensional small sample size data. In Chapter 2, we propose a likelihood ratio test framework for testing normal mean vectors in high-dimensional data under two common scenarios: the one-sample test and the two-sample test with equal covariance matrices. We derive the test statistics under the assumption that the covariance matrices follow a diagonal matrix structure. In comparison with the diagonal Hotelling's tests, our proposed test statistics display some interesting characteristics. In particular, they are a summation of the log-transformed squared t-statistics rather than a direct summation of those components. More importantly, to derive the asymptotic normality of our test statistics under the null and local alternative hypotheses, we do not need the requirement that the covariance matrices follow a diagonal matrix structure. As a consequence, our proposed test methods are very flexible and readily applicable in practice. Monte Carlo simulations and a real data analysis are also carried out to demonstrate the advantages of the proposed methods. In Chapter 3, we propose a pairwise Hotelling's method for testing high-dimensional mean vectors. The new test statistics make a compromise on whether using all the correlations or completely abandoning them. To achieve the goal, we perform a screening procedure, pick up the paired covariates with strong correlations, and construct a classical Hotelling's statistic for each pair. While for the individual covariates without strong correlations with others, we apply squared t statistics to account for their respective contributions to the multivariate testing problem. As a consequence, our proposed test statistics involve a combination of the collected pairwise Hotelling's test statistics and squared t statistics. The asymptotic normality of our test statistics under the null and local alternative hypotheses are also derived under some regularity conditions. Numerical studies and two real data examples demonstrate the efficacy of our pairwise Hotelling's test. In Chapter 4, we propose a regularized t distribution and also explore its applications in multiple testing. The motivation of this topic dates back to microarray studies, where the expression levels of thousands of genes are measured simultaneously by the microarray technology. To identify genes that are differentially expressed between two or more groups, one needs to conduct hypothesis test for each gene. However, as microarray experiments are often with a small number of replicates, Student's t-tests using the sample means and standard deviations may suffer a low power for detecting differentially expressed genes. To overcome this problem, we first propose a regularized t distribution and derive its statistical properties including the probability density function and the moments. The noncentral regularized t distribution is also introduced for the power analysis. To demonstrate the usefulness of the proposed test, we apply the regularized t distribution to the gene expression detection problem. Simulation studies and two real data examples show that the regularized t-test outperforms the existing tests including Student's t-test and the Bayesian t-test in a wide range of settings, in particular when the sample size is small.
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 Applications and Power Analysis of New Multiple Testing Procedures Based on the Covering Principle by : Yu Zhang
Download or read book Applications and Power Analysis of New Multiple Testing Procedures Based on the Covering Principle written by Yu Zhang and published by . This book was released on 2021 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple comparison tests are quite prevalent in clinical trials to increase efficiency and the chance of finding treatment or drug effects. However, making multiple comparisons will lead to the potential inflation of the Type I error rate. How well one test procedure controls the rate of false-positive conclusions becomes the main concern nowadays. A novel method named Covering Principle has been proposed recently. It provides a new approach to designing multiple testing procedures from the angle of rejection regions in the sample space, rather than in the parameter space, which uses in the methods based on the closed testing and partitioning principle. This paper presented several cases studies and a simulation study using Holm's, Fixed and Fallback based on the Covering Principle. Meanwhile, the power comparison results between the Covering Principle and the graphical method are exhibited and analyzed in this paper.
Book Synopsis Simultaneous Statistical Inference by : Thorsten Dickhaus
Download or read book Simultaneous Statistical Inference written by Thorsten Dickhaus and published by Springer Science & Business Media. This book was released on 2014-01-23 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
Book Synopsis Group Sequential Methods with Applications to Clinical Trials by : Christopher Jennison
Download or read book Group Sequential Methods with Applications to Clinical Trials written by Christopher Jennison and published by CRC Press. This book was released on 1999-09-15 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Group sequential methods answer the needs of clinical trial monitoring committees who must assess the data available at an interim analysis. These interim results may provide grounds for terminating the study-effectively reducing costs-or may benefit the general patient population by allowing early dissemination of its findings. Group sequential methods provide a means to balance the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion. Group Sequential Methods with Applications to Clinical Trials describes group sequential stopping rules designed to reduce average study length and control Type I and II error probabilities. The authors present one-sided and two-sided tests, introduce several families of group sequential tests, and explain how to choose the most appropriate test and interim analysis schedule. Their topics include placebo-controlled randomized trials, bio-equivalence testing, crossover and longitudinal studies, and linear and generalized linear models. Research in group sequential analysis has progressed rapidly over the past 20 years. Group Sequential Methods with Applications to Clinical Trials surveys and extends current methods for planning and conducting interim analyses. It provides straightforward descriptions of group sequential hypothesis tests in a form suited for direct application to a wide variety of clinical trials. Medical statisticians engaged in any investigations planned with interim analyses will find this book a useful and important tool.
Book Synopsis Handbook of Multiple Comparisons by : Xinping Cui
Download or read book Handbook of Multiple Comparisons written by Xinping Cui and published by CRC Press. This book was released on 2021-11-18 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control and insights on how principles developed earlier can be applied to current and emerging problems. Some highlights of the coverages are as follows. Error rate control is useful for controlling the incorrect decision rate. Chapter 1 introduces Tukey's original multiple comparison error rates and point to how they have been applied and adapted to modern multiple comparison problems as discussed in the later chapters. Principles endure. While the closed testing principle is more familiar, Chapter 4 shows the partitioning principle can derive confidence sets for multiple tests, which may become important as the profession goes beyond making decisions based on p-values. Multiple comparisons of treatment efficacy often involve multiple doses and endpoints. Chapter 12 on multiple endpoints explains how different choices of endpoint types lead to different multiplicity adjustment strategies, while Chapter 11 on the MCP-Mod approach is particularly useful for dose-finding. To assess efficacy in clinical trials with multiple doses and multiple endpoints, the reader can see the traditional approach in Chapter 2, the Graphical approach in Chapter 5, and the multivariate approach in Chapter 3. Personalized/precision medicine based on targeted therapies, already a reality, naturally leads to analysis of efficacy in subgroups. Chapter 13 draws attention to subtle logical issues in inferences on subgroups and their mixtures, with a principled solution that resolves these issues. This chapter has implication toward meeting the ICHE9R1 Estimands requirement. Besides the mere multiple testing methodology itself, the handbook also covers related topics like the statistical task of model selection in Chapter 7 or the estimation of the proportion of true null hypotheses (or, in other words, the signal prevalence) in Chapter 8. It also contains decision-theoretic considerations regarding the admissibility of multiple tests in Chapter 6. The issue of selected inference is addressed in Chapter 9. Comparison of responses can involve millions of voxels in medical imaging or SNPs in genome-wide association studies (GWAS). Chapter 14 and Chapter 15 provide state of the art methods for large scale simultaneous inference in these settings.
Book Synopsis Multiple Testing Procedures and Simultaneous Interval Estimates with the Interval Property by : Yingqiu Ma
Download or read book Multiple Testing Procedures and Simultaneous Interval Estimates with the Interval Property written by Yingqiu Ma and published by . This book was released on 2012 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of step-wise multiple testing procedures arises because single step procedures are extremely conservative. Research into the construction of useful, computationally feasible interval estimates corresponding to step-wise procedures has been slow. We present an alternative method of constructing multiple testing procedures that easily admits corresponding interval estimates. The new approach has the desirable interval property not usually shared by step-wise procedures. Furthermore, the new method take dependency into account and easily carried out. In addition, these intervals are typically shorter, less likely to contain the null point falsely, and are more informative than those based on traditional methods. Applications include treatments vs control, change point and all pairwise comparisons. Examples and simulations are included.
Book Synopsis Multiple Comparisons Using R by : Frank Bretz
Download or read book Multiple Comparisons Using R written by Frank Bretz and published by CRC Press. This book was released on 2016-04-19 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org After giving examples of multiplicity problems, the book covers general concepts and basic multiple comparisons procedures, including the Bonferroni method and Simes’ test. It then shows how to perform parametric multiple comparisons in standard linear models and general parametric models. It also introduces the multcomp package in R, which offers a convenient interface to perform multiple comparisons in a general context. Following this theoretical framework, the book explores applications involving the Dunnett test, Tukey’s all pairwise comparisons, and general multiple contrast tests for standard regression models, mixed-effects models, and parametric survival models. The last chapter reviews other multiple comparison procedures, such as resampling-based procedures, methods for group sequential or adaptive designs, and the combination of multiple comparison procedures with modeling techniques. Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice versa. See Dr. Bretz discuss the book.
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 Dose Finding in Drug Development by : Naitee Ting
Download or read book Dose Finding in Drug Development written by Naitee Ting and published by Springer Science & Business Media. This book was released on 2006-12-29 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you have ever wondered when visiting the pharmacy how the dosage of your prescription is determined this book will answer your questions. Dosing information on drug labels is based on discussion between the pharmaceutical manufacturer and the drug regulatory agency, and the label is a summary of results obtained from many scientific experiments. The book introduces the drug development process, the design and the analysis of clinical trials. Many of the discussions are based on applications of statistical methods in the design and analysis of dose response studies. Important procedural steps from a pharmaceutical industry perspective are also examined.
Book Synopsis Multiple Comparisons in Truncated Group Sequential Experiments with Applications in Clinical Trials by : Tian Zhao
Download or read book Multiple Comparisons in Truncated Group Sequential Experiments with Applications in Clinical Trials written by Tian Zhao and published by . This book was released on 2015 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid growth of the pharmaceutical industry, it became particularly important to develop efficient statistical techniques for conducting clinical trials. Practically clinical trials nowadays are conducted to answer many questions rather than exploring just one hypothesis. A treatment has to pass the efficacy and safety standards minimally. Handling multiplicity in clinical trials has become a hot topic. During the last two decades, a number of new statistical techniques appeared that improved the overall power of multiple testing procedures while still controlling the familywise Type I error rate. However, a large portion of modern clinical trials is conducted sequentially. The last five years or so, Bartroff and Lai, De and Baron, applied stepwise testing of multiple hypotheses. The procedures were open-ended. But the standard practice requires any clinical trials to be completed by the given date. Any stopping rules have to be truncated. This is the main difference in the problem considered in this dissertation from all the previously proposed methods. In this dissertation, we derived the simultaneous testing of multiple hypotheses that: - control the familywise Type I and Type II error rates; - terminate sampling with probability one at or before the given number of sampled groups; - optimize the expected sample size. For the purpose of testing multiple hypotheses, with a given truncation point, we developed a new group sequential procedure based on the truncated sequential probability ratio test. Our method resulted in an improved single-hypothesis testing that appeared to be more efficient than Pollock's method proposed earlier for the same problem. Extending this to multiple hypotheses by means of Holm-Bonferroni stepwise approach, we derive a truncated group sequential procedure for the simultaneous testing of multiple hypotheses that controls familywise Type I and Type II errors in the strong sense. The new methods can be applied to any truncated sequential sampling for multiple comparisons. Optimizing the expected sampling cost of a clinical trial in this context inevitably implies reduction in the cost of medical treatments, and therefore, it ultimately results in the reduced cost of health care.
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 Understanding Statistics and Experimental Design by : Michael H. Herzog
Download or read book Understanding Statistics and Experimental Design written by Michael H. Herzog and published by Springer. This book was released on 2019-08-13 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
