Free Ebook Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace
There is no question that book Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace will certainly constantly offer you inspirations. Also this is just a book Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace; you could locate several categories and types of publications. From captivating to experience to politic, as well as sciences are all given. As just what we state, here our company offer those all, from famous writers as well as publisher worldwide. This Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace is among the collections. Are you interested? Take it now. Exactly how is the means? Find out more this article!
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace
Free Ebook Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace
Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace Exactly how can you change your mind to be more open? There lots of sources that could assist you to enhance your ideas. It can be from the other encounters as well as story from some individuals. Schedule Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace is one of the trusted resources to get. You can discover plenty books that we discuss here in this web site. As well as currently, we show you one of the most effective, the Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace
When getting this publication Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace as recommendation to check out, you could gain not just motivation yet also brand-new knowledge and also driving lessons. It has even more compared to common benefits to take. What type of book that you read it will work for you? So, why must get this book qualified Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace in this short article? As in link download, you could get the e-book Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace by on the internet.
When getting the publication Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace by online, you could read them wherever you are. Yeah, also you are in the train, bus, hesitating checklist, or other areas, online book Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace could be your great friend. Whenever is a great time to review. It will improve your expertise, fun, entertaining, driving lesson, and experience without investing more cash. This is why on the internet publication Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace ends up being most really wanted.
Be the first which are reviewing this Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace Based upon some reasons, reviewing this e-book will certainly provide even more benefits. Also you require to review it detailed, page by page, you could finish it whenever and also wherever you have time. Once again, this on-line publication Applied Meta-Analysis With R (Chapman & Hall/CRC Biostatistics Series), By Ding-Geng (Din) Chen, Karl E. Peace will give you simple of reading time and task. It likewise supplies the experience that is economical to reach as well as acquire significantly for much better life.
In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R.
Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data.
Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R) in public health, medical research, governmental agencies, and the pharmaceutical industry.
- Sales Rank: #1566874 in Books
- Published on: 2013-05-03
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x .90" w x 6.20" l, 1.40 pounds
- Binding: Hardcover
- 342 pages
Review
"This book is one of the first books introducing how to use R packages and functions for meta-analyses. … a well-written book suitable for graduate students and practitioners in the fields of medicine and health. It gives updated information for R packages and meta-analysis. The detailed, step-by-step explanations make this book a nice reference, especially for self-study learners."
―Biometrics, September 2015
"… this is the first book about meta-analysis which exclusively uses R … Although the book is listed under the biostatistics series and the examples are built around medical data sets, the book is accessible for those in the social sciences with a quantitative interest as well. … the authors present the output of the R functions as well as the results of step-by-step implementations in R. This approach helps R users as well as meta-analysis novices to gain a deeper understanding of the subject matter."
―Psychometrika, Vol. 80, June 2015
"… this book may be a suitable text for learning metadata analysis, particularly for students seeking degrees in statistics or biostatistics. This book should equally serve as a valuable reference regarding self-study and learning tool for related practitioners and biostatisticians, particularly those with little or no experience in using R. Overall, this is a clearly written and sequentially well-organized book. One may find it easy to read and comprehend the various conceptual and methodological issues related to meta-analysis and their applicability using R. To facilitate better understanding, each of the commonly used methods is covered with illustration using real data sets. … one of the best referrals especially as a metaanalysis reference book to younger researchers/biostatisticians. … an important source to acquire desired statistical skills regarding meta-analysis, with a focus on their applications using R and interpretation. Further, it may be equally helpful in scientific understanding of related research articles and their critical appraisal."
―ISCB News, 59, June 2015
"Chen and Peace’s book adds to a growing number of resources for practitioners of meta-analysis that include short courses, specialty software, and textbooks devoted to the subject. What distinguishes Applied Meta-Analysis with R (AMAR) is its focus on the use of R, the current language of choice for many biostatisticians and students of biostatistics. Chen and Peace’s writing style mixes explanatory text with numerous step-by-step programming examples. The examples are taken from real clinical applications, including Dr. Steven Nissen’s controversial synthesis of rosiglitazone trials (2007). The examples that pepper the text help to demonstrate the usefulness of meta-analysis, while also addressing some of the practical challenges, such as rare event data, that can arise in real applications. ... As the first applied text on meta-analysis in R, practitioners will find AMAR a useful though imperfect attempt to fill an important gap in their library."
―Journal of Biopharmaceutical Statistics, 2015
"Various primers on research synthesis have been written in the past decade, but probably none with such a clear emphasis on software application. The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis. … A strength of the book, especially from an applied user’s point of view, is that the authors do not get lost in technical details. … a useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs."
―Journal of Applied Statistics, 2014
"… especially valuable to medical researchers in universities, industries, or governmental agencies. For beginners who are not familiar with the R system and meta-analysis, this book can also serve as a good guide and reference … an outstanding feature of this book is that it presents plenty of concise R codes and corresponding outputs, with clear comments explaining the meaning of the codes. Currently, a great deal of literature has been devoted to meta-analysis, but most of them usually introduce theoretics and carry out the analysis only presenting the results, such as estimated odds ratio and forest plots. This book not only makes readers aware of why the meta-analysis approaches are derived, but also provides excellent practical skills to synthesize different clinical trials. … I recommend this book as a nice reference for beginners and researchers who are interested in meta-analysis."
―Journal of the American Statistical Association, December 2014
About the Author
Ding-Geng (Din) Chen, Ph.D., is a professor at the University of Rochester Medical Center. Dr. Chen has vast experience in biostatistical research and clinical trial development and methodology. He has authored or co-authored more than 100 journal publications on biostatistical methodologies and applications. He is also the co-author (with Dr. Peace) of Clinical Trial Methodology and Clinical Trial Data Analysis Using R and a co-editor (with Drs. Sun and Peace) of Interval-Censored Time-to-Event Data: Methods and Applications. He is a member of the American Statistical Association, chair for the STAT section of the American Public Health Association, an associate editor of the Journal of Statistical Computation and Simulation, and an editorial board member of several other journals.
Karl E. Peace, Ph.D., is the Georgia Cancer Coalition Distinguished Cancer Scholar, senior research scientist, and professor of biostatistics in the Jiann-Ping Hsu College of Public Health at Georgia Southern University. He is also an adjunct professor of biostatistics at the VCU School of Medicine. Dr. Peace is a reviewer or editor of several journals, the founding editor of the Journal of Biopharmaceutical Statistics, and a fellow of the American Statistical Association. He has authored or co-authored over 150 articles and 10 books. He has received numerous awards, including the University System of Georgia Board of Regents’ Alumni Hall of Fame Award, the First President’s Medal for outstanding contributions to Georgia Southern University, and distinguished meritorious service awards from the American Public Health Association and other organizations. In 2012, the American Statistical Association created the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Review: Applied Meta-Analysis with R
By Oscar Linares, MD
I highly recommend this book to anyone doing meta-analysis in general, and meta-analysis with R, in particular. The book brings you up to speed quickly and the examples are relevant to actual research. Using R for meta-analysis in this book is like "standing on the shoulders of giants" as one does their work on meta-analysis.
Oscar A. Linares, MD
Mathematical Medicine & Biostatistics Unit
Plymouth Pharmacokinetic Modeling Study Group
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace PDF
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace EPub
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace Doc
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace iBooks
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace rtf
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace Mobipocket
Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series), by Ding-Geng (Din) Chen, Karl E. Peace Kindle
Tidak ada komentar:
Posting Komentar