Download or read book Meta Tags written by Samuel Blankson and published by Lulu.com. This book was released on 2007 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: Buying a Web site is only the start of finding success on the Internet. Being found by Web users on Google, Yahoo!, MSN, AltaVista, AOL, Alltheweb, Fast, GigaBlast, Netscape, Snap, WISEnut, and thousands of other search engines is the next major hurdle. This edition describes how to optimize Web sites titles, headings, Meta Tags, and more to maximize the effectiveness of how search engines view and rank the Web sites relevance to keyword searches. (Computer Books - Internet)
Download or read book Methods of Meta Analysis written by John E Hunter and published by SAGE. This book was released on 2004-04-07 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the most important developments in meta-analysis from 1990 to 2004, this text presents new patterns in research findings as well as updated information on existing topics.
Download or read book Meta Analytic Procedures for Social Research written by Robert Rosenthal and published by SAGE. This book was released on 1991-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praised in the first edition for the clarity of his general framework for conceptualizing meta-analysis, Rosenthal's revised edition covers the latest techniques in the field, such as a new effect size indicator for one size data, a new coefficient of robustness of replication, new procedures for combining and comparing effect sizes for multiple dependent variables, and new data on the magnitude of the problem of incomplete retrieval (the file drawer problem).
Download or read book Meta Learning written by Lan Zou and published by Elsevier. This book was released on 2022-11-05 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep neural networks (DNNs) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta-learning with DNNs brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve, even transcending what they can achieve. Meta-Learning: Theory, Algorithms and Applications shows how meta-learning in combination with DNNs advances towards AGI. Meta-Learning: Theory, Algorithms and Applications explains the fundamentals of meta-learning by providing answers to these questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use meta-learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta-learning, few-shot learning, deep learning, transfer learning, machine learning, probabilistic modeling, and Bayesian inference. It then explains important state-of-the-art mechanisms and their variants for meta-learning, including memory-augmented neural networks, meta-networks, convolutional Siamese neural networks, matching networks, prototypical networks, relation networks, LSTM meta-learning, model-agnostic meta-learning, and the Reptile algorithm. The book takes a deep dive into nearly 200 state-of-the-art meta-learning algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR, ACL, ICLR, KDD). It systematically investigates 39 categories of tasks from 11 real-world application fields: Computer Vision, Natural Language Processing, Meta-Reinforcement Learning, Healthcare, Finance and Economy, Construction Materials, Graphic Neural Networks, Program Synthesis, Smart City, Recommended Systems, and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources. Meta-Learning: Theory, Algorithms and Applications is a great resource to understand the principles of meta-learning and to learn state-of-the-art meta-learning algorithms, giving the student, researcher and industry professional the ability to apply meta-learning for various novel applications. A comprehensive overview of state-of-the-art meta-learning techniques and methods associated with deep neural networks together with a broad range of application areas Coverage of nearly 200 state-of-the-art meta-learning algorithms, which are promoted by premier global AI conferences and journals, and 300 to 450 pieces of key research Systematic and detailed exploration of the most crucial state-of-the-art meta-learning algorithm mechanisms: model-based, metric-based, and optimization-based Provides solutions to the limitations of using deep learning and/or machine learning methods, particularly with small sample sizes and unlabeled data Gives an understanding of how meta-learning acts as a stepping stone to Artificial General Intelligence in 39 categories of tasks from 11 real-world application fields
Download or read book Modern Meta Analysis written by Ton J. Cleophas and published by Springer. This book was released on 2017-05-02 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern meta-analyses do more than combine the effect sizes of a series of similar studies. Meta-analyses are currently increasingly applied for any analysis beyond the primary analysis of studies, and for the analysis of big data. This 26-chapter book was written for nonmathematical professionals of medical and health care, in the first place, but, in addition, for anyone involved in any field involving scientific research. The authors have published over twenty innovative meta-analyses from the turn of the century till now. This edition will review the current state of the art, and will use for that purpose the methodological aspects of the authors' own publications, in addition to other relevant methodological issues from the literature. Are there alternative works in the field? Yes, there are, particularly in the field of psychology. Psychologists have invented meta-analyses in 1970, and have continuously updated methodologies. Although very interesting, their work, just like the whole discipline of psychology, is rather explorative in nature, and so is their focus to meta-analysis. Then, there is the field of epidemiologists. Many of them are from the school of angry young men, who publish shocking news all the time, and JAMA and other publishers are happy to publish it. The reality is, of course, that things are usually not as bad as they seem. Finally, some textbooks, written by professional statisticians, tend to use software programs with miserable menu programs and requiring lots of syntax to be learnt. This is prohibitive to clinical and other health professionals. The current edition is the first textbook in the field of meta-analysis entirely written by two clinical scientists, and it consists of many data examples and step by step analyses, mostly from the authors' own clinical research.
Download or read book Meta Analysis written by Mike W.-L. Cheung and published by John Wiley & Sons. This book was released on 2015-04-07 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.
Download or read book Publication Bias in Meta Analysis written by Hannah R. Rothstein and published by John Wiley & Sons. This book was released on 2006-02-03 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or methodological quality. It can arise from selective publication of favorable results, or of statistically significant results. This threatens the validity of conclusions drawn from reviews of published scientific research. Meta-analysis is now used in numerous scientific disciplines, summarizing quantitative evidence from multiple studies. If the literature being synthesised has been affected by publication bias, this in turn biases the meta-analytic results, potentially producing overstated conclusions. Publication Bias in Meta-Analysis examines the different types of publication bias, and presents the methods for estimating and reducing publication bias, or eliminating it altogether. Written by leading experts, adopting a practical and multidisciplinary approach. Provides comprehensive coverage of the topic including: Different types of publication bias, Mechanisms that may induce them, Empirical evidence for their existence, Statistical methods to address them, Ways in which they can be avoided. Features worked examples and common data sets throughout. Explains and compares all available software used for analysing and reducing publication bias. Accompanied by a website featuring software, data sets and further material. Publication Bias in Meta-Analysis adopts an inter-disciplinary approach and will make an excellent reference volume for any researchers and graduate students who conduct systematic reviews or meta-analyses. University and medical libraries, as well as pharmaceutical companies and government regulatory agencies, will also find this invaluable.
Download or read book Meta X written by Umweltforschungszentrum Leipzig-Halle and published by Springer Science & Business Media. This book was released on 2003 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: "META-X is a user-friendly computer program that allows students, teachers, and researchers to perform a metapopulation viability analysis i.e. to assess the extinction risk of (meta) populations on discrete, partially isolated patches of habitat, in a comfortable way. The CD comes with an extensive handbook which explains the basic concept of the program and takes you on a guided tour through a model experiment. It further provides the necessary scientific background on both metapopulation dynamics and population viability analysis." "A special feature of META-X is that it supports comparative analyses of alternative scenarios. This predestines META-X to serve as an aid for decision making in conservation management and landscape planning. Furthermore, handbook and software together provide an invaluable help in research and teaching."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved
Download or read book Introduction to Meta Platforms written by Gilad James, PhD and published by Gilad James Mystery School. This book was released on with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Meta regression Analysis in Economics and Business written by T. D. Stanley and published by Routledge. This book was released on 2012 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-Regression Analysis in Economics and Business is the first text devoted to the meta-regression analysis (MRA) of economics and business research.
Download or read book Methods of Meta Analysis written by Frank L. Schmidt and published by SAGE Publications. This book was released on 2014-02-05 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to provide researchers clear and informative insight into techniques of meta-analysis, the Third Edition of Methods of Meta-Analysis: Correcting Error and Bias in Research Findings is the most comprehensive text on meta-analysis available today. It is the only book that presents a full and usable treatment of the role of study artifacts in distorting study results, as well as methods for correcting results for such biases and errors. Meta-analysis is arguably the most important methodological innovation in the last thirty-five years, due to its immense impact on the development of cumulative knowledge and professional practice. This text, now in its updated Third Edition, has been revised to cover the newest developments in meta-analysis methods, evaluation, correction, and more. This reader-friendly book is the definitive resource on meta-analysis. “This text is the primary source text for psychometric meta-analysis methods.” —Emily E. Tanner-Smith, Vanderbilt University “The key strength of the book is the complete and thorough coverage of psychometric meta-analysis. This technique is not covered in any other meta-analysis text, and is a major contribution to the literature…The meta-analysis field needs to find ways to integrate Hunter and Schmidt’s methods into current meta-analysis practice.” —Terri D. Pigott, Loyola University of Chicago “This is an important text. It is the only book that presents adequate coverage of psychometric meta-analysis. In addition to its use as a textbook, it is an invaluable resource for anyone involved in meta-analytic studies.” —Steven Pulos, University of Northern Colorado
Download or read book Meta analysis written by Catherine Selden and published by . This book was released on 1992 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Meta Analysis written by Shahjahan Khan and published by Springer Nature. This book was released on 2020-10-27 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on performing hands-on meta-analysis using MetaXL, a free add-on to MS Excel. The illustrative examples are taken mainly from medical and health sciences studies, but the generic methods can be used to perform meta-analysis on data from any other discipline. The book adopts a step-by-step approach to perform meta-analyses and interpret the results. Stata codes for meta-analyses are also provided. All popularly used meta-analytic methods and models – such as the fixed effect model, random effects model, inverse variance heterogeneity model, and quality effect model – are used to find the confidence interval for the effect size measure of independent primary studies and the pooled study. In addition to the commonly used meta-analytic methods for various effect size measures, the book includes special topics such as meta-regression, dose-response meta-analysis, and publication bias. The main attraction for readers is the book’s simplicity and straightforwardness in conducting actual meta-analysis using MetaXL. Researchers would easily find everything on meta-analysis of any particular effect size in one specific chapter once they could determine the underlying effect measure. Readers will be able to see the results under different models and also will be able to select the correct model to obtain accurate results.
Download or read book Meta Learning in Computational Intelligence written by Norbert Jankowski and published by Springer Science & Business Media. This book was released on 2011-06-10 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Download or read book Advanced BASIC Meta analysis written by Brian Mullen and published by Psychology Press. This book was released on 1989 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1989. Routledge is an imprint of Taylor & Francis, an informa company.
Download or read book Meta level Inference Systems written by Frank Van Harmelen and published by Morgan Kaufmann. This book was released on 1991 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Meta Analysis Decision Analysis and Cost Effectiveness Analysis written by Diana B. Petitti and published by Oxford University Press. This book was released on 1999-10-14 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of evidence-based medicine. These related quantitative methods have become essential tools in the formulation of clinical and public policy based on the synthesis of evidence. All three methods are taught with increasing frequency in medical schools and schools of public health and in health policy courses at the undergraduate and graduate level. This book is a lucid introduction, and will serve the needs of students taking introductory courses that cover these topics. It will also be useful to clinicians and policymakers who need to understand the quantitative underpinnings of the methods in order to best apply the information that derives from them. The second edition of this popular book adds new material on cumulative meta-analysis as a method to explore heterogeneity. The coverage of cost-effectiveness analysis has been brought into close alignment with recommendations of the U.S. Public Health Panel on Cost-Effectiveness Analysis in Health and Medicine. Many of the examples have been replaced with more current examples, and all of the material has been updated to reflect recent advances in the methods and the emergence of consensus about some previously controversial issues. analysis. These three closely related methods have become even more important for synthesizing research since the first edition was published in 1994. And they have gained legitimacy as tools for guiding health policy.
