Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Comparing The Empirical Likelihood Ratio Test And The Likelihood Ratio Test full books in PDF, epub, and Kindle. Read online Comparing The Empirical Likelihood Ratio Test And The Likelihood Ratio Test ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Shana Leigh Carter
Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (435 download)
Download or read book Comparing the Empirical Likelihood Ratio Test and the Likelihood Ratio Test written by Shana Leigh Carter and published by . This book was released on 1999 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : 侯科宇
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (1 download)
Download or read book Empirical Likelihood Ratio Tests for Two Sample Comparison Under Current Status Data written by 侯科宇 and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : 許玳瑜
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (15 download)
Download or read book Empirical Likelihood Ratio Tests with Smoothing Estimators and a Weighted Approach for Two Sample Comparison Under Current Status Data written by 許玳瑜 and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : 洪于景
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (1 download)
Download or read book Two Sample Comparison Based on Empirical Likelihood Ratio Test for Right Censored Data written by 洪于景 and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Paul Shen
Publisher :
ISBN 13 :
Total Pages : 19 pages
Book Rating : 4.:/5 (11 download)
Download or read book EMPIRICAL LIKELIHOOD TESTS FOR CONSTANT VARIANCE IN THE TWO-SAMPLE PROBLEM written by Paul Shen and published by . This book was released on 2019 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we investigate the problem of testing constant variance. It is an important problem in the field of statistical influence where many methods require the assumption of constant variance. The question of constant variance has to be settled in order to perform a significance test through a Student t-Test or an F-test. Two of most popular tests of constant variance in applications are the classic F-test and the Modified Levene's Test. The former is a ratio of two sample variances. Its performance is found to be very sensitive with the normality assumption. The latter Modified Levene's Test can be viewed as a result of the estimation method through the absolute deviation from the median. Its performance is also dependent upon the distribution shapes to some extent, though not as much as the F-test. We propose an innovative test constructed by the empirical likelihood method through the moment estimation equations appearing in the Modified Levene's Test. The new empirical likelihood ratio test is a nonparametric test and retains the principle of maximum likelihood. As a result, it can be an appropriate alternative to the two traditional tests in applications when underlying populations are skewed. To be specific, the empirical likelihood ratio test of constant variance uses the optimal weights in summing the absolute deviations of observations from the median values, while the Modified Levene's test uses the simple averages. It is thus desired that the empirical likelihood ratio test is more powerful than the Modified Levene's test. Meanwhile, the empirical likelihood ratio test is expected to be as robust as the Modified Levene's test, as the empirical likelihood ratio test is also constructed via the same distance as the Modified Levene's test. A real-life data set is used to illustrate implementation of the empirical likelihood ratio test with comparisons to the classic F-test and the Modified Levene's Test. It is confirmed that the empirical likelihood ratio test performs the best.
Author : Albert Vexler
Publisher : CRC Press
ISBN 13 : 1351001515
Total Pages : 300 pages
Book Rating : 4.3/5 (51 download)
Download or read book Empirical Likelihood Methods in Biomedicine and Health written by Albert Vexler and published by CRC Press. This book was released on 2018-09-03 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data. Provides a systematic overview of novel empirical likelihood techniques. Presents a good balance of theory, methods, and applications. Features detailed worked examples to illustrate the application of the methods. Includes R code for implementation. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.
Author : Geert Molenberghs
Publisher : Springer Science & Business Media
ISBN 13 : 9780387251448
Total Pages : 720 pages
Book Rating : 4.2/5 (514 download)
Download or read book Models for Discrete Longitudinal Data written by Geert Molenberghs and published by Springer Science & Business Media. This book was released on 2006-08-30 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.
Author : Art B. Owen
Publisher : CRC Press
ISBN 13 : 1420036157
Total Pages : 322 pages
Book Rating : 4.4/5 (2 download)
Download or read book Empirical Likelihood written by Art B. Owen and published by CRC Press. This book was released on 2001-05-18 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It al
Author : Albert Vexler
Publisher : CRC Press
ISBN 13 : 1351001507
Total Pages : 149 pages
Book Rating : 4.3/5 (51 download)
Download or read book Empirical Likelihood Methods in Biomedicine and Health written by Albert Vexler and published by CRC Press. This book was released on 2018-09-03 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data. Provides a systematic overview of novel empirical likelihood techniques. Presents a good balance of theory, methods, and applications. Features detailed worked examples to illustrate the application of the methods. Includes R code for implementation. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.
Author : 李均鵬
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (1 download)
Download or read book Maximum Likelihood Estimation and Empirical Likelihood Ratio Test Under Semi-competing Risks Data written by 李均鵬 and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Richard Royall
Publisher : Routledge
ISBN 13 : 1351414550
Total Pages : 212 pages
Book Rating : 4.3/5 (514 download)
Download or read book Statistical Evidence written by Richard Royall and published by Routledge. This book was released on 2017-11-22 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.
Author : Richard L. Dykstra
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (31 download)
Download or read book A Robust Nonparametric Likelihood Ratio Test written by Richard L. Dykstra and published by . This book was released on 1981 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: The likelihood ratio principle is employed to suggest a nonparametric test for testing equality of two distributions against a stochastic ordering alternative. The test appears to be robust against a wide range of alternatives. Percentage points for sample sizes less than or equal to twenty are provided as well as a comparison of power values for the Kolmogorov-Smirnov and Mann-Whitney-Wilcoxon tests. (Author).
Author : William H. Barton
Publisher :
ISBN 13 :
Total Pages : 157 pages
Book Rating : 4.:/5 (94 download)
Download or read book Comparison of Two Samples by a Nonparametric Likelihood-ratio Test written by William H. Barton and published by . This book was released on 2010 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Albert Vexler
Publisher : CRC Press
ISBN 13 : 1315353016
Total Pages : 622 pages
Book Rating : 4.3/5 (153 download)
Download or read book Statistical Testing Strategies in the Health Sciences written by Albert Vexler and published by CRC Press. This book was released on 2017-12-19 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging from graphical methods and classical procedures through computationally intensive bootstrap strategies to advanced empirical likelihood techniques. It bridges the gap between theoretical statistical methods and practical procedures applied to the planning and analysis of health-related experiments. The book is organized primarily based on the type of questions to be answered by inference procedures or according to the general type of mathematical derivation. It establishes the theoretical framework for each method, with a substantial amount of chapter notes included for additional reference. It then focuses on the practical application for each concept, providing real-world examples that can be easily implemented using corresponding statistical software code in R and SAS. The book also explains the basic elements and methods for constructing correct and powerful statistical decision-making processes to be adapted for complex statistical applications. With techniques spanning robust statistical methods to more computationally intensive approaches, this book shows how to apply correct and efficient testing mechanisms to various problems encountered in medical and epidemiological studies, including clinical trials. Theoretical statisticians, medical researchers, and other practitioners in epidemiology and clinical research will appreciate the book’s novel theoretical and applied results. The book is also suitable for graduate students in biostatistics, epidemiology, health-related sciences, and areas pertaining to formal decision-making mechanisms.
Author : Christian Tönsing
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)
Download or read book Likelihood-ratio Test Statistic for the Finite-sample Case in Nonlinear Ordinary Differential Equation Models written by Christian Tönsing and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Likelihood ratios are frequently utilized as basis for statistical tests, for model selection criteria and for assessing parameter and prediction uncertainties, e.g. using the profile likelihood. However, translating these likelihood ratios into p-values or confidence intervals requires the exact form of the test statistic's distribution. The lack of knowledge about this distribution for nonlinear ordinary differential equation (ODE) models requires an approximation which assumes the so-called asymptotic setting, i.e. a sufficiently large amount of data. Since the amount of data from quantitative molecular biology is typically limited in applications, this finite-sample case regularly occurs for mechanistic models of dynamical systems, e.g. biochemical reaction networks or infectious disease models. Thus, it is unclear whether the standard approach of using statistical thresholds derived for the asymptotic large-sample setting in realistic applications results in valid conclusions. In this study, empirical likelihood ratios for parameters from 19 published nonlinear ODE benchmark models are investigated using a resampling approach for the original data designs. Their distributions are compared to the asymptotic approximation and statistical thresholds are checked for conservativeness. It turns out, that corrections of the likelihood ratios in such finite-sample applications are required in order to avoid anti-conservative results
Author : Charles M. Judd
Publisher : Routledge
ISBN 13 : 1136874100
Total Pages : 329 pages
Book Rating : 4.1/5 (368 download)
Download or read book Data Analysis written by Charles M. Judd and published by Routledge. This book was released on 2011-03-15 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. The authors show how all analysis of variance and multiple regression can be accomplished within this framework. The model-comparison approach provides several benefits: It strengthens the intuitive understanding of the material thereby increasing the ability to successfully analyze data in the future It provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of questions It reduces the number of statistical techniques that must be memorized It teaches readers how to become data analysts instead of statisticians. The book opens with an overview of data analysis. All the necessary concepts for statistical inference used throughout the book are introduced in Chapters 2 through 4. The remainder of the book builds on these models. Chapters 5 - 7 focus on regression analysis, followed by analysis of variance (ANOVA), mediational analyses, non-independent or correlated errors, including multilevel modeling, and outliers and error violations. The book is appreciated by all for its detailed treatment of ANOVA, multiple regression, nonindependent observations, interactive and nonlinear models of data, and its guidance for treating outliers and other problematic aspects of data analysis. Intended for advanced undergraduate or graduate courses on data analysis, statistics, and/or quantitative methods taught in psychology, education, or other behavioral and social science departments, this book also appeals to researchers who analyze data. A protected website featuring additional examples and problems with data sets, lecture notes, PowerPoint presentations, and class-tested exam questions is available to adopters. This material uses SAS but can easily be adapted to other programs. A working knowledge of basic algebra and any multiple regression program is assumed.
Author : Mai Zhou
Publisher : CRC Press
ISBN 13 : 1466554932
Total Pages : 221 pages
Book Rating : 4.4/5 (665 download)
Download or read book Empirical Likelihood Method in Survival Analysis written by Mai Zhou and published by CRC Press. This book was released on 2015-06-17 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Likelihood Method in Survival Analysis explains how to use the empirical likelihood method for right censored survival data. The author uses R for calculating empirical likelihood and includes many worked out examples with the associated R code. The datasets and code are available for download on his website and CRAN. The book focuses on all the standard survival analysis topics treated with empirical likelihood, including hazard functions, cumulative distribution functions, analysis of the Cox model, and computation of empirical likelihood for censored data. It also covers semi-parametric accelerated failure time models, the optimality of confidence regions derived from empirical likelihood or plug-in empirical likelihood ratio tests, and several empirical likelihood confidence band results. While survival analysis is a classic area of statistical study, the empirical likelihood methodology has only recently been developed. Until now, just one book was available on empirical likelihood and most statistical software did not include empirical likelihood procedures. Addressing this shortfall, this book provides the functions to calculate the empirical likelihood ratio in survival analysis as well as functions related to the empirical likelihood analysis of the Cox regression model and other hazard regression models.
