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Meta-Analysis with R
This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.
Cochrane Handbook for Systematic Reviews of Interventions
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 revie...
Matrix Inequalities for Iterative Systems
The book reviews inequalities for weighted entry sums of matrix powers. Applications range from mathematics and CS to pure sciences. It unifies and generalizes several results for products and powers of sesquilinear forms derived from powers of Hermitian, positive-semidefinite, as well as nonnegative matrices. It shows that some inequalities are valid only in specific cases. How to translate the Hermitian matrix results into results for alternating powers of general rectangular matrices? Inequalities that compare the powers of the row and column sums to the row and column sums of the matrix powers are refined for nonnegative matrices. Lastly, eigenvalue bounds and derive results for iterated kernels are improved.
Robust and Multivariate Statistical Methods
This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.
Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy
Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy A guide to conducting systematic reviews of test accuracy In Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy, a team of distinguished researchers deliver the official guide to preparing and maintaining systematic reviews of test accuracy in healthcare. This first edition of the Handbook contains guidance on understanding test accuracy measures, search strategies and study selection, understanding meta-analysis and risk of bias and applicability assessments, presentation of findings, and drawing conclusions. Readers will also find: An introduction to test evaluation, including the purposes of medical tes...
Meta-Analysis for Public Management and Policy
Praise for Meta-Analysis for Public Management and Policy "In his usual rigorous but readable style, Evan Ringquist and co-author Mary Anderson have produced a tour-de-force on the topic of meta-analysis in public policy and management research. Meta-analysis is badly needed in the all-too-common situation when researchers have low confidence in summarizing the overall results of dozens of studies on the effectiveness of some policy. This book has a nice combination of conceptual overview, methodological details, and applications that will make it possible for researchers to conduct their own meta-analysis. It is tempting to require all graduate students to write a meta-analysis as a chapter...
The Fragmented Personality
The Fragmented Personality presents new model for caring for patients with personality disorder in post-modern society. In contrast to the static classifications of personality pathology, the authors' approach yields a personalized diagnosis that is contextual, dimensional, and time-specific and at the same time provides information about the current position of the individual in relation to the important components of personality functioning. In this model of dimensional diagnostics, two intersecting coordinates, one representing the person's level of functioning (the "what" of the diagnosis) and the other his/her adaptive style (the "how" of the diagnosis) are cross matched in the unit of ...
The Impact of Mindfulness Meditation Programs on Performance-Related Outcomes
This report presents results from a systematic review and meta-analyses of research examining how mindfulness meditation affects 13 performance-related outcomes of interest to the U.S. Army and broader military. The authors supplemented the systematic review by examining how mindfulness meditation could support stress management and exploring characteristics of selected mindfulness programs.
Practicing Trustworthy Machine Learning
With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable. Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. You'll learn: Methods to explain ML models and their outputs to stakeholders How to recognize and fix fairness concerns and privacy leaks in an ML pipeline How to develop ML systems that are robust and secure against malicious attacks Important systemic considerations, like how to manage trust debt and which ML obstacles require human intervention
Ministry with Persons with Mental Illness and Their Families
In Ministry with Persons with Mental Illness and Their Families, psychiatrists and pastoral theologians come together in an interdisciplinary, collaborative effort to ensure accuracy of information concerning the medical dimensions of mental illness, interpret these illnesses from a faith perspective, and make suggestions relative to effective ministry. Readers will learn how science and a faith tradition can not only co-exist but work in tandem to alleviate the pain of the afflicted and affected.
