Download or read book Testing Hypotheses Under Covariate adaptive Randomization in Linear and Generalized Linear Models written by and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The covariate-adaptive randomization methods have been proposed for sequential experiments in clinical trials for a long time, but very little theoretical work has been done for statistical inference under these randomization schemes. Because of the unavailability of a valid test procedure associated with covariate-adaptive randomization, practitioners often apply test procedures developed for simple randomization, which is controversial since procedures valid under simple randomization may not be valid under covariate-adaptive randomization. In this thesis, we provide some theoretical results for testing hypotheses under covariate-adaptive randomization. It is demonstrated that one way to obtain a valid test procedure under covariate-adaptive randomization is to construct a test valid under any fixed treatment allocation conditionally on covariates including the one used in covariate-adaptive randomization. In addition, the simple two sample t-test without using any covariate is proved to be conservative in terms of its Type I error rate under covariate-adaptive biased coin randomization for both linear models and generalized linear models. As a remedy, a valid bootstrap t-test is constructed. This bootstrap test, utilizing covariate in the randomization scheme, is shown to be asymptotically as efficient as Wald's test using covariates in the analysis when the model between covariates and response is correctly specified. Thus, the efficiency loss due to not using covariates in the analysis is recovered by using covariates in covariate-adaptive biased coin randomization through bootstrap. The powers of several tests under covariate-adaptive biased coin randomization and simple randomization are examined and compared theoretically as well as empirically. Our study provides guidance for applications and sheds light on further research in this area.

Download or read book Modern Adaptive Randomized Clinical Trials written by Oleksandr Sverdlov and published by CRC Press. This book was released on 2015-06-30 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials? What kind of statistical inference should be used to achieve valid and unbiased treatment comparisons following adaptive random

Download or read book Testing Research Hypotheses with the General Linear Model written by Keith A. McNeil and published by SIU Press. This book was released on 1996 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Briefly describes 777 serial bibliographies relating to modern literature in most of the major languages. Chapters cover comprehensive bibliographies, those for English and foreign literatures, for topics from African American studies to women's studies, and for particular authors. The 1982 edition has been updated and expanded to include information on electronic serial bibliographies. Paper edition (unseen), $19.75. Annotation copyright by Book News, Inc., Portland, OR

Download or read book Sample Size Choice written by Robert E. Odeh and published by CRC Press. This book was released on 2020-08-12 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to testing statistical hypotheses for readers familiar with the Neyman-Pearson theory of hypothesis testing including the notion of power, the general linear hypothesis (multiple regression) problem, and the special case of analysis of variance. The second edition (date of first not mentione

Download or read book Statistical Inference for Adaptive Designs in Multi center Clinical Trials written by Selvakkadunko Selvaratnam and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We discuss methods for comparing effects of two treatments A and B. We investigate the performance of response-adaptive (RA) and covariate-adjusted response-adaptive (CARA) designs in multi-center clinical trials. First, we discuss applying RA designs to maximize the well-being of participating patients in multi-center clinical trials. We assume that the centers are selected from a large population of centers and develop a generalized linear mixed model (GLMM) to examine the treatment effect. The asymptotic properties of the maximum likelihood (ML) estimators of model parameters are derived using the in uence function method. We verified their theoretical properties through simulation studies. The techniques are then applied to a real data that were obtained from a multi-center clinical trial designed to compare two cream preparations (active drug/control) for treating an infection. Secondly, we investigate the efficiency for estimates of model parameters and ethics for participating patients among RA, CARA, and completely randomized (CR) designs for a generalized linear model (GLM). We consider the logit model to measure efficiency and ethics. Furthermore, we showed that ML estimators of GLM parameters are consistent and asymptotically follow multivariate normal distribution for adaptive designs. A simulation study was conducted to verify these theoretical results. Finally, we provide a justification of why asymptotic results for Wald-type tests for adaptive designs can be used. We proved that the choice of adaptive designs affects the statistical power of hypothesis testing via these quantities: the target allocation proportion, the bias of the randomization procedure from the target, and the variability induced by the randomization process. Moreover, we showed that the statistical power increases when the design variability decreases for a covariate in a logit model. Our theoretical findings are verified by simulation results.

Download or read book Practical Considerations for Adaptive Trial Design and Implementation written by Weili He and published by Springer. This book was released on 2014-10-15 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is a definitive text on adaptive clinical trial designs from creation and customization to utilization. As this book covers the full spectrum of topics involved in the adaptive designs arena, it will serve as a valuable reference for researchers working in industry, government and academia. The target audience is anyone involved in the planning and execution of clinical trials, in particular, statisticians, clinicians, pharmacometricians, clinical operation specialists, drug supply managers, and infrastructure providers. In spite of the increased efficiency of adaptive trials in saving costs and time, ultimately getting drugs to patients sooner, their adoption in clinical development is still relatively low. One of the chief reasons is the higher complexity of adaptive design trials as compared to traditional trials. Barriers to the use of clinical trials with adaptive features include the concerns about the integrity of study design and conduct, the risk of regulatory non-acceptance, the need for an advanced infrastructure for complex randomization and clinical supply scenarios, change management for process and behavior modifications, extensive resource requirements for the planning and design of adaptive trials and the potential to relegate key decision makings to outside entities. There have been limited publications that address these practical considerations and recommend best practices and solutions. This book fills this publication gap, providing guidance on practical considerations for adaptive trial design and implementation. The book comprises three parts: Part I focuses on practical considerations from a design perspective, whereas Part II delineates practical considerations related to the implementation of adaptive trials. Putting it all together, Part III presents four illustrative case studies ranging from description and discussion of specific adaptive trial design considerations to the logistic and regulatory issues faced in trial implementation. Bringing together the expertise of leading key opinion leaders from pharmaceutical industry, academia, and regulatory agencies, this book provides a balanced and comprehensive coverage of practical considerations for adaptive trial design and implementation.

Download or read book Statistics in Precision Health written by Yichuan Zhao and published by Springer Nature. This book was released on with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Some Hypothesis Testing Results for Two way Linear Models in Clinical Trials written by Bin Cheng and published by . This book was released on 2004 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Design and Analysis of Experiments Volume 3 written by Klaus Hinkelmann and published by John Wiley & Sons. This book was released on 2012-02-14 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.

Download or read book On Criteria for Testing Linear Hypotheses in Regression Models written by N. Ramesh Kumar and published by LAP Lambert Academic Publishing. This book was released on 2014-01 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this present book Chapter I is an introductory one. It contains the general introduction about the importance of hypotheses testing in econometrics. Chapter II deals with the inferential aspects of linear models. It describes the various problems of the theory of Econometrics. Chapter III describes the existing criteria for testing general linear hypotheses in the linear models. It contains the derivation and applications of Restricted Least Squares estimation in the theory of Econometrics.Chapter IV proposes same alternative criteria for testing general linear hypotheses in the generalized linear models. Mean Squared Error (MSE) criteria have been explained for testing general linear hypotheses in the generalized linear models under the problems of heteroscedasticity and singular linear models.Chapter V gives the conclusions of the book .Several relavant articles regarding the Hypotheses testing in linear regression models have been presented under a title 'BIBLIOGRAPHY'

Download or read book Hypothesis Testing Under Stratified Community based Cluster Randomized Trials with a Small Number of Clusters written by and published by . This book was released on 2013 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster randomized trials (CRTs) are experiments in which clusters of people, or intact social units, rather than individuals are randomized into either intervention or control groups. The key feature of CRTs is that outcomes on individuals in the same cluster tend to be correlated. Hence standard analytical methods that assume individuals within a cluster are independent will have a tendency to underestimate the standard error of the treatment difference and inflate type I error, which lead to overstate the significance of the results. In addition, for randomization at cluster lever, it is quite common to find a large imbalance on important factors between treatment groups, especially when only a few clusters are randomized. In order to reduce the imbalance risk and keep the study as effective and precise as possible, in this thesis, we employed the stratification design under CRTs, investigated and compared the performance of six methods. These methods include (1) unadjusted Mantel-Haenszel test; (2) adjusted Mantel-Haenszel test; (3) cluster level t test; (4) two-stage covariates adjusted cluster level t test; (5) generalized estimating equations (GEE) and (6) generalized linear mixed model method (GLMM). Empirical Type I errors and powers for the different methods considered are evaluated using Monte Carlo simulation over a wide range of scenarios, including very small numbers of clusters, which are commonly used in practice. Furthermore, the choice of an appropriate number of strata for the study design is also discussed. Based on our simulation results, the two-stage covariates adjusted t test outperformed other methods in terms of empirical significance and power levels when the number of clusters is small. We further illustrated these approaches by applying real life data collected from a community-based cluster randomized trial, in which the outcome measure was the knowledge of HIV acquisition.

Download or read book Clinical Trial Design written by Guosheng Yin and published by John Wiley & Sons. This book was released on 2012-01-03 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics. Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include: Risk and benefit analysis for toxicity and efficacy trade-offs Bayesian predictive probability trial monitoring Bayesian adaptive randomization Late onset toxicity and response Dose finding in drug combination trials Targeted therapy designs The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials. Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.

Download or read book Topics on Multiple Hypotheses Testing and Generalized Linear Model written by Yalin Zhu and published by . This book was released on 2017 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: In applications such as studying drug adverse events (AE) in clinical trials and identifying differentially expressed genes in microarray experiments, the data of the experiments usually consists of frequency counts. In the analysis of such data, researchers often face multiple hypotheses testing based on discrete test statistics. Incorporating this discrete property of the data, several stepwise procedures, which allow to use the CDF of p-values to determine the testing threshold, are proposed for controlling familiwise error rate (FWER). It is shown that the proposed procedures strongly control the FWER and are more powerful than the existing ones for discrete data. Through some simulation studies and real data examples, the proposed procedures are shown to outperform the existing procedures in terms of the FWER control and power. An R package “MHTdiscrete” and a web application are developed for implementing the proposed procedures for discrete data.

Download or read book Randomization in Clinical Trials written by William F. Rosenberger and published by John Wiley & Sons. This book was released on 2015-11-23 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “All medical statisticians involved in clinical trials should read this book...” - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, simplify the mathematics, and ease readers’ understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition, also published by Wiley.

Download or read book Testing Hypotheses in Linear Models with Weighted Rank Statistics written by G. L. Sievers and published by . This book was released on 1983 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tests of hypotheses for the parameters in a general linear model are considered based on weighted rank statistics. Results are presented for tests based on a rank estimate, tests based on drop in dispersion and aligned rank tests. Weights can be used to focus the analysis on simple effects and provide an additional degree of robustness to rank tests. Several analysis of variance applications are discussed. (Author).

Download or read book Tests of Hypotheses in Fixed Effects Linear Models written by J. H. Goodnight and published by . This book was released on 1978 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On Likelihood Ratio Tests of One sided Hypotheses in Generalized Linear Models with Canonical Links written by Mervyn J. Silvapulle and published by . This book was released on 1990 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: