Download or read book Statistical Methods for Combining Diagnostic Tests and Performance Evaluation Metrics written by Chengning Zhang (Ph.D.) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In biomedical studies, it is usually the case that several diagnostic tests can be performedon an individual or multiple disease markers are available simultaneously, and that many of them may be associated with the clinical outcome. In practice, a single test or marker often has limited diagnostic performance. Therefore, it is important to combine multiple sources of information available to achieve higher classification performance. This dissertation focuses on statistical methods for combining multiple diagnostic tests and the corresponding performance evaluation metrics. In the first project, we provide a survey of the current state of the art in methods for combining multiple tests. We categorize existing methods into three general groups and conduct extensive simulation studies to compare the performance of different combination methods. The reviewed methods serve as benchmark for developing new combination approaches in the following projects. In the second project, we consider the problem of combining multiple tests whose values are missing at random (MAR). In addition, we aim to exploit the known monotonicity relationship between the input variables and the disease outcome for gains in diagnostic accuracy. We develop a novel likelihood-based approach to monotone classification that accounts for missing inputs in a natural and principled way. The risk score function is obtained through the nonparametric maximum likelihood estimation (NPMLE). A novel expectation-maximization (EM)-type algorithm is devised to compute the NPMLE by treating the monotonicity-constrained risk score function as a cumulative distribution for a latent random vector. Through simulation studies and a real data example, we demonstrate that the proposed method outperforms state-of-the-art methods for combining multiple inputs under monotonic assumption, especially when the inputs contain missing data. We illustrate our approach with a dataset from a recent nonalcoholic fatty liver disease (NALFD) study. In the third project, our approach established in the second part is extended to the scenario where one covariate is randomly censored. The proposed approach consists of two steps. In step one, we use a Cox proportional hazards model for the distribution of the censored covariate given other covariates in the model, this conditional distribution is used for calculating the observed likelihood of data. In step two, a similar expectation maximization (EM)-type algorithm is devised, based on observed data likelihood from step one, to compute the NPMLE of the monotonicity-constrained risk score function. Through simulation studies, we demonstrate that the proposed method outperforms the simple but inefficient complete-case analysis as well as the substitution methods. We apply our method to the data set from a primary biliary cirrhosis (PBC) study conducted at Mayo Clinic. The proposed methods in part two and three can be extended to multi-class cases, where the labels have an inherent order but no meaningful numeric distance between them. A natural question arises as to how to evaluate the classification performance under such setting. Therefore, in the fourth project, we consider the problem of performance evaluation metrics for ordinal classification. We propose three novel performance evaluation metrics that better capture the ordinality of the outcomes. The first metric is adapted from the area under the receiver operating characteristic (ROC) curve (AUC), while the latter two are simple and interpretable generalizations of the Harrell's concordance index (C-INDEX). Moreover, we show the optimality of the AUC based metrics through Neyman-Pearson lemma. We conduct extensive simulation studies to confirm the usefulness of the proposed performance metrics for ordinal classification.
Download or read book Statistical Methods for Performance Evaluation and Their Applications written by Longzhuang Li and published by . This book was released on 2002 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical performance evaluation has many applications. In these applications, many alternative solutions or hypotheses exist and the ones performing the best in terms of predetermined measurements are sought. The performance measures of hypotheses are numerical numbers and have to be obtained based on examples and may contain noise. In addition, due to the time and resource constraints in real applications, it is often impractical or even impossible to evaluate all hypotheses. Thus, statistical metrics are used to evaluate the performance of hypotheses efficiently using a limited number of examples and tests. There are many statistical metrics available and their results depends on many factors, such as the number of test cases, whether or not the performance measurements are noisy, and the distribution of performance measurements of the hypotheses. Selecting the most appropriate statistical metrics is a challenging task. In this dissertation, we propose a general framework for statistical performance evaluation. The framework incorporates various statistical metrics and automatically selects the most appropriate one based on the characteristics of the application problem. We have identified the following important problem characteristics: the number of hypotheses, the size of sample data for each hypothesis, the distribution of performance measurements, and the distribution of noise in performance measurements. Then, we apply statistical performance evaluation methods to four applications: evaluation of search engine performance on the Web, analysis and improvement of HITS-based document ranking algorithms, optimization design of filter banks for image compression, and optimization design of filter banks for signal denoising. In the first application, we apply statistical methods to evaluate the precision of search engines. We have performed extensive experiments using real search engines on the Web and obtained promising results. In the second application, we statistically analyze the performance of the combination of HITS-based algorithms and relevance scoring methods, and develop a adaptive weighting method which achieves better results without any content analysis. In the third application, we develop an optimization-based approach to design biorthogonal filter banks for image compression, in which statistical performance evaluation methods are used to select the solutions that are more generalizable to other images unseen in the optimization design stage. Similarly, in the fourth application, we develop an optimization-based method for designing orthonormal filter banks for signal denoising and apply statistical performance evaluation methods in selecting more generalizable solutions. In these two applications, our methods have obtained filter banks that perform better than the benchmark existing filter banks.
Download or read book Evaluation of Diagnostic Systems written by John Swets and published by Academic Press. This book was released on 1982-01-28 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evaluation of Diagnostic Systems: Methods from Signal Detection Theory addresses the many issues that arise in evaluating the performance of a diagnostic system, across the wide range of settings in which such systems are used. These settings include clinical medicine, industrial quality control, environmental monitoring and investigation, machine and metals inspection, military monitoring, information retrieval, and crime investigation. The book is divided into three parts encompassing 11 chapters that emphasize the interpretation of diagnostic visual images by human observers. The first part of the book describes quantitative methods for measuring the accuracy of a system and the statistical techniques for drawing inferences from performance tests. The subsequent part covers study design and includes a detailed description of the form and conduct of an image-interpretation test. The concluding part examines the case study of a medical imaging system that serves as an example of both simple and complex applications. In this part, three mammographic modalities are used: industrial film radiography, low-dose film radiography, and xeroradiography. The case study focuses on the overall reliability of accuracy indices made by its main components, that is, the variabilities across cases, across readers, and within individual readers. The supplementary texts provide study protocols, a computer program for processing test results, and an extensive list of references that will assist the reader in applying those evaluative methods to diagnostic systems in any setting. This book is of value to scientists and engineers, as well as to applied, quantitative, or experimental psychologists who are engaged in the study of the human processes of discrimination and decision making in either perceptual or cognitive tasks.
Download or read book Finite Mixture Models written by Geoffrey McLachlan and published by John Wiley & Sons. This book was released on 2004-03-22 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, comprehensive account of major issues in finitemixture modeling This volume provides an up-to-date account of the theory andapplications of modeling via finite mixture distributions. With anemphasis on the applications of mixture models in both mainstreamanalysis and other areas such as unsupervised pattern recognition,speech recognition, and medical imaging, the book describes theformulations of the finite mixture approach, details itsmethodology, discusses aspects of its implementation, andillustrates its application in many common statisticalcontexts. Major issues discussed in this book include identifiabilityproblems, actual fitting of finite mixtures through use of the EMalgorithm, properties of the maximum likelihood estimators soobtained, assessment of the number of components to be used in themixture, and the applicability of asymptotic theory in providing abasis for the solutions to some of these problems. The author alsoconsiders how the EM algorithm can be scaled to handle the fittingof mixture models to very large databases, as in data miningapplications. This comprehensive, practical guide: * Provides more than 800 references-40% published since 1995 * Includes an appendix listing available mixture software * Links statistical literature with machine learning and patternrecognition literature * Contains more than 100 helpful graphs, charts, and tables Finite Mixture Models is an important resource for both applied andtheoretical statisticians as well as for researchers in the manyareas in which finite mixture models can be used to analyze data.
Download or read book Diagnostic Tests Toolkit written by Matthew Thompson and published by John Wiley & Sons. This book was released on 2011-09-29 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diagnostic Tests Toolkit Diagnostic Tests Toolkit Finding the evidence for diagnostic tests Establishing an evidence-based methodology to assess the effectiveness of diagnostic tests has posed problems for many years. Now that the framework is in place health professionals can find and appraise the evidence for themselves. With Diagnostic Tests Toolkit clinicians and junior researchers can interpret the evidence for the effectiveness of different types of diagnostic tests, or develop their own research using the successful ‘step-by-step’ format of the Toolkit series. Written by renowned clinical researchers, this is the first basic guide to evidence-based diagnosis. It is equally valuable to starters in clinical research and those needing a quick refresher on the core elements of evidence-based diagnosis.
Download or read book Statistical Evaluation of Diagnostic Performance written by Kelly H. Zou and published by CRC Press. This book was released on 2016-04-19 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are releva
Download or read book Journal of the National Cancer Institute written by and published by . This book was released on 2008 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improving Diagnosis in Health Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2015-12-29 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.
Download or read book Introduction to Statistical Methods in Pathology written by Amir Momeni and published by Springer. This book was released on 2017-09-07 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides a comprehensive and practical review of the main statistical methods in pathology and laboratory medicine. It introduces statistical concepts used in pathology and laboratory medicine. The information provided is relevant to pathologists both for their day to day clinical practice as well as in their research and scholarly activities. The text will begins by explaining the fundamentals concepts in statistics. In the later sections, these fundamental concepts are expanded and unique applications of statistical methods in pathology and laboratory medicine practice are introduced. Other sections of the text explain research methodology in pathology covering a broad range of topics from study design to analysis of data. Finally, data-heavy novel concepts that are emerging in pathology and pathology research are presented such as molecular pathology and pathology informatics. Introduction to Statistical Methods in Pathology will be of great value for pathologists, pathology residents, basic and translational researchers, laboratory managers and medical students.
Download or read book Principles and Practice of Clinical Trials written by Steven Piantadosi and published by Springer Nature. This book was released on 2022-07-19 with total page 2573 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference.
Download or read book Least Squares Support Vector Machines written by Johan A. K. Suykens and published by World Scientific. This book was released on 2002 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpretations from optimization theory. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LS-SVM models is discussed, together with methods for imposing spareness and employing robust statistics. The framework is further extended towards unsupervised learning by considering PCA analysis and its kernel version as a one-class modelling problem. This leads to new primal-dual support vector machine formulations for kernel PCA and kernel CCA analysis. Furthermore, LS-SVM formulations are given for recurrent networks and control. In general, support vector machines may pose heavy computational challenges for large data sets. For this purpose, a method of fixed size LS-SVM is proposed where the estimation is done in the primal space in relation to a Nystrom sampling with active selection of support vectors. The methods are illustrated with several examples.
Download or read book An Empirical Assessment of Bivariate Methods for Meta Analysis of Test Accuracy written by U. S. Department of Health and Human Services and published by Createspace Independent Pub. This book was released on 2013-03-21 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical tests are used every day for guiding diagnosis, predicting the future course of disease, and guiding treatment selection. The effects of tests on clinical outcomes are indirect, through their influence on physicians' diagnostic thinking and treatment decisionmaking. Comparative studies of testing versus no testing that can answer the overarching question of test effectiveness (clinical utility) are rarely performed. Because of this, assessment of medical tests often relies only on the evaluation of test “accuracy,” or test performance, typically measured by sensitivity and specificity (clinical validity of tests). Even when studies of clinical utility are available, systematic reviews of test performance are an important component of any comprehensive evidence assessment of a medical test. In most cases tests are used to classify patients into two mutually exclusive and exhaustive groups (“test positive” and “test negative”)—positive test results indicate that patients are more likely to have the condition of interest and should be targeted for additional diagnostic investigation or considered for therapeutic intervention. In such cases, test accuracy can be expressed as the ability to identify individuals with disease as “test positives” (sensitivity) and individuals with no disease as “test negatives” (specificity). Additional accuracy metrics, such as the area under the receiver operating characteristic (ROC) curve, the diagnostic odds ratio, or the Q* statistic (the point on the ROC curve where sensitivity equals specificity), are often reported in primary studies. Individual studies of test accuracy tend to be small and are often conducted in diverse settings. Systematic reviews of medical test studies offer a natural framework for evidence synthesis. When the aim is to increase precision or quantitatively assess the impact of study-level characteristics on test sensitivity or specificity, meta-analytic methods can be used to combine the results of independent studies into summary estimates of accuracy or to identify modifiers of accuracy through meta-regression. Meta-analysis of studies of test accuracy presents several challenges to systematic reviewers. First, meta-analysis of sensitivity and specificity requires modeling a multivariate outcome (sensitivity and specificity reported from each study). Second, joint modeling of sensitivity and specificity needs to take into account the correlation of these estimates across studies induced by threshold effects. Third, studies often produce heterogeneous results, necessitating the use of random effects models when the interest is to generalize beyond the observed data. Analyses that fail to take into account threshold effects or between-study variability may produce incompatible estimates of sensitivity and specificity or spuriously precise estimates of test accuracy. This report is the second in a series of three on meta-analysis of test accuracy, conducted by the Tufts Evidence-based Practice Center under contract with the Agency for Healthcare Research and Quality (AHRQ). For the current project we sought to perform a large-scale empirical comparison of alternative meta-analysis methods for sensitivity and specificity and for constructing SROC curves. This report addresses the following aims by using a previously established database of meta-analytic datasets: Compare univariate (one outcome at a time) and bivariate (joint analysis of two outcomes) methods for meta-analysis of sensitivity and specificity; Compare inverse variance (DerSimonian-Laird), maximum likelihood (ML) and Bayesian methods for random effects meta-analysis of sensitivity and specificity; Compare methods using a normal approximation versus those using the exact binomial likelihood for meta-analysis of sensitivity and specificity; Compare alternative statistical models for constructing meta-analytic SROC curves.
Download or read book Statistical Methods in Diagnostic Medicine written by Xiao-Hua Zhou and published by John Wiley & Sons. This book was released on 2014-08-21 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition " . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."—Zentralblatt MATH A new edition of the cutting-edge guide to diagnostic tests in medical research In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include: Methods for tests designed to detect and locate lesions Recommendations for covariate-adjustment Methods for estimating and comparing predictive values and sample size calculations Correcting techniques for verification and imperfect standard biases Sample size calculation for multiple reader studies when pilot data are available Updated meta-analysis methods, now incorporating random effects Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS®, and R software packages so that readers can conduct their own analyses. Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.
Download or read book Systematic Reviews in Health Care written by Matthias Egger and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this best-selling book has been thoroughly revised and expanded to reflect the significant changes and advances made in systematic reviewing. New features include discussion on the rationale, meta-analyses of prognostic and diagnostic studies and software, and the use of systematic reviews in practice.
Download or read book Cochrane Handbook for Systematic Reviews of Interventions written by Julian P. T. Higgins and published by Wiley. This book was released on 2008-11-24 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves.
Download or read book Statistical Methods in Water Resources written by D.R. Helsel and published by Elsevier. This book was released on 1993-03-03 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources. The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies. The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
Download or read book The Evidence Base of Clinical Diagnosis written by J. Andre Knottnerus and published by BMJ Books. This book was released on 2009-01-26 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book presents a framework for the strategy and methodology of diagnostic research, in relation to its relevance for practice. Now in its second edition The Evidence Base of Clinical Diagnosis has been fully revised and extended with new chapters covering the STARD guidelines (STAndards for the Reporting of Diagnostic accuracy studies) and the multivariable analysis of diagnostic data. With contributions from leading international experts in evidence-based medicine, this book is an indispensable guide on how to conduct and interpret studies in clinical diagnosis. It will serve as a valuable resource for all investigators who want to embark on diagnostic research and for clinicians, practitioners and students who want to learn more about its principles and the relevant methodological options available.
