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 Meta Regression Analysis in Economics and Business written by T.D. Stanley and published by Routledge. This book was released on 2012-08-21 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to introduce novice researchers to the tools of meta-analysis and meta-regression analysis and to summarize the state of the art for existing practitioners. Meta-regression analysis addresses the rising "Tower of Babel" that current economics and business research has become. Meta-analysis is the statistical analysis of previously published, or reported, research findings on a given hypothesis, empirical effect, phenomenon, or policy intervention. It is a systematic review of all the relevant scientific knowledge on a specific subject and is an essential part of the evidence-based practice movement in medicine, education and the social sciences. However, research in economics and business is often fundamentally different from what is found in the sciences and thereby requires different methods for its synthesis—meta-regression analysis. This book develops, summarizes, and applies these meta-analytic methods.
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 2012-08-21 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to introduce novice researchers to the tools of meta-analysis and meta-regression analysis and to summarize the state of the art for existing practitioners. Meta-regression analysis addresses the rising "Tower of Babel" that current economics and business research has become. Meta-analysis is the statistical analysis of previously published, or reported, research findings on a given hypothesis, empirical effect, phenomenon, or policy intervention. It is a systematic review of all the relevant scientific knowledge on a specific subject and is an essential part of the evidence-based practice movement in medicine, education and the social sciences. However, research in economics and business is often fundamentally different from what is found in the sciences and thereby requires different methods for its synthesis—meta-regression analysis. This book develops, summarizes, and applies these meta-analytic methods.
Download or read book Meta Regression Analysis written by Colin Roberts and published by Wiley-Blackwell. This book was released on 2006-01-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume celebrates the innovative and rapidly growing area of economic research known as meta-regression analysis (MRA). Shows how MRA enables researchers to make sense of disparate economic findings on the same subject. Develops methods that help researchers to distinguish publication selection from genuine empirical effect. Applies these methods to topical areas of economic research including: the effect of immigration on wages, minimum wage on unemployment, and gender on salaries. Helps to bridge the gulf between economic theory and practice. Written to be accessible to readers with a basic background in empirical economics.
Download or read book The Economics of Trade Unions written by Hristos Doucouliagos and published by Routledge. This book was released on 2017-02-17 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Richard B. Freeman and James L. Medoff’s now classic 1984 book What Do Unions Do? stimulated an enormous theoretical and empirical literature on the economic impact of trade unions. Trade unions continue to be a significant feature of many labor markets, particularly in developing countries, and issues of labor market regulations and labor institutions remain critically important to researchers and policy makers. The relations between unions and management can range between cooperation and conflict; unions have powerful offsetting wage and non-wage effects that economists and other social scientists have long debated. Do the benefits of unionism exceed the costs to the economy and society writ large, or do the costs exceed the benefits? The Economics of Trade Unions offers the first comprehensive review, analysis and evaluation of the empirical literature on the microeconomic effects of trade unions using the tools of meta-regression analysis to identify and quantify the economic impact of trade unions, as well as to correct research design faults, the effects of selection bias and model misspecification. This volume makes use of a unique dataset of hundreds of empirical studies and their reported estimates of the microeconomic impact of trade unions. Written by three authors who have been at the forefront of this research field (including the co-author of the original volume, What Do Unions Do?), this book offers an overview of a subject that is of huge importance to scholars of labor economics, industrial and employee relations, and human resource management, as well as those with an interest in meta-analysis.
Download or read book Econometrics For Dummies written by Roberto Pedace and published by John Wiley & Sons. This book was released on 2013-06-05 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Score your highest in econometrics? Easy. Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics. Econometrics For Dummies breaks down this complex subject and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations. An excellent resource for anyone participating in a college or graduate level econometrics course Provides you with an easy-to-follow introduction to the techniques and applications of econometrics Helps you score high on exam day If you're seeking a degree in economics and looking for a plain-English guide to this often-intimidating course, Econometrics For Dummies has you covered.
Download or read book Applied Statistics and Multivariate Data Analysis for Business and Economics written by Thomas Cleff and published by Springer. This book was released on 2019-07-10 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.
Download or read book Meta Analysis with R written by Guido Schwarzer and published by Springer. This book was released on 2015-10-08 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applied Meta Analysis for Social Science Research written by Noel A. Card and published by Guilford Publications. This book was released on 2015-10-06 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs. ÿ
Download or read book Philosophy of Science and Meta Knowledge in International Business and Management written by Timothy M. Devinney and published by Emerald Group Publishing. This book was released on 2013-06-25 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores major issues and concepts in the field of international business and management and asks the question 'What is it that we know?' It examines key topics such as multinational enterprise and strategic management theory, post-merger integration, internalizing firms and the strategy-performance relationship.
Download or read book Statistical Methods for Meta Analysis written by Larry V. Hedges and published by Academic Press. This book was released on 2014-06-28 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
Download or read book Applied Regression Analysis for Business and Economics written by Terry E. Dielman and published by Brooks/Cole. This book was released on 2001 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for undergraduate and MBA courses in regression analysis for business and economics, this text requires very little mathematical expertise beyond college algebra. Terry Dielman emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets.
Download or read book Presenting Medical Statistics from Proposal to Publication written by Janet L. Peacock and published by Oxford University Press. This book was released on 2017-07-21 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: As many medical and healthcare researchers have a love-hate relationship with statistics, the second edition of this practical reference book may make all the difference. Using practical examples, mainly from the authors' own research, the book explains how to make sense of statistics, turn statistical computer output into coherent information, and help decide which pieces of information to report and how to present them. The book takes you through all the stages of the research process, from the initial research proposal, through ethical approval and data analysis, to reporting on and publishing the findings. Helpful tips and information boxes, offer clear guidance throughout, including easily followed instructions on how to: -develop a quantitative research proposal for ethical/institutional approval or research funding -write up the statistical aspects of a paper for publication -choose and perform simple and more advanced statistical analyses -describe the statistical methods and present the results of an analysis. This new edition covers a wider range of statistical programs - SAS, STATA, R, and SPSS, and shows the commands needed to obtain the analyses and how to present it, whichever program you are using. Each specific example is annotated to indicate other scenarios that can be analysed using the same methods, allowing you to easily transpose the knowledge gained from the book to your own research. The principles of good presentation are also covered in detail, from translating relevant results into suitable extracts, through to randomised controlled trials, and how to present a meta-analysis. An added ingredient is the inclusion of code and datasets for all analyses shown in the book on our website (http://medical-statistics.info). Written by three experienced biostatisticians based in the UK and US, this is a step-by-step guide that will be invaluable to researchers and postgraduate students in medicine, those working in the professions allied to medicine, and statisticians in consultancy roles.
Download or read book Advances in Spatial Econometrics written by Luc Anselin and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Download or read book Handbook of Meta Analysis written by Christopher H. Schmid and published by CRC Press. This book was released on 2020-09-07 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Provides a comprehensive overview of meta-analysis methods and applications. 2. Divided into four major sub-topics, covering univariate meta-analysis, multivariate, applications and policy. 3. Designed to be suitable for graduate students and researchers new to the field. 4. Includes lots of real examples, with data and software code made available. 5. Chapters written by the leading researchers in the field.
Download or read book Network Meta Analysis for Decision Making written by Sofia Dias and published by John Wiley & Sons. This book was released on 2018-03-19 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best'?" A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.
