Meta-Analysis in Stata, Tom M. Palmer and Jonathan A. C. Sterne (editors)
Старое издание
Автор: Kohler Название: Data Analysis Using Stata, Third Edition ISBN: 1597181102 ISBN-13(EAN): 9781597181105 Издательство: Taylor&Francis Рейтинг: Цена: 11176.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.
The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.
Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.
Автор: Boyhan Название: Agricultural Statistical Data Analysis Using Stata ISBN: 1466585854 ISBN-13(EAN): 9781466585850 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Practical statistics is a powerful tool used frequently by agricultural researchers and graduate students involved in investigating experimental design and analysis. One of the most widely used statistical analysis software packages for this purpose is Stata. The Stata software program has matured into a user-friendly environment with a wide variety of statistical functions. Agricultural Statistical Data Analysis Using Stata introduces readers to the use of Stata to solve agricultural statistical problems.
The book begins with an overview of statistical software and the Stata program. It explains the various windows and menus and describes how they are integrated. The next chapters explore data entry and importing as well as basic output formats and descriptive statistics. The author describes the ever-increasing design complexity and how this is implemented in the software. He reviews one of Stata's strongest features, which is its programming ability. He also examines post hoc tests as well as Stata's graphing capabilities. The final chapters provide information on regression analysis, data transformations, and the analyses of non-parametric data.
Many agricultural researchers are unprepared for the statistics they will need to use in their profession. Written in an easy-to-read format with screen shots and illustrations, the book is suitable for a wide audience, including beginners in statistics who are new to Stata, as well as more advanced Stata users and those interested in more complex designs.
Автор: Arthur, Jr. Название: Conducting Meta-Analysis Using SAS ISBN: 0805838090 ISBN-13(EAN): 9780805838091 Издательство: Taylor&Francis Рейтинг: Цена: 6123.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed to teach the reader about meta-analysis and show them how to conduct one using SAS. Its focus is more applied and practical than theoretical and will include additional programming codes and examples. Web site to house program code and sample ou
Автор: Kulinskaya, E Morgenthaler, Stephan Staudte, Rober Название: Meta analysis ISBN: 0470028645 ISBN-13(EAN): 9780470028643 Издательство: Wiley Рейтинг: Цена: 10130.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments. The authors aim to promote a deeper understanding of the notion of statistical evidence. The book is comprised of two parts - The Handbook, and The Theory.
Автор: Koricheva Julia Название: Handbook of Meta-Analysis in Ecology and Evolution ISBN: 0691137293 ISBN-13(EAN): 9780691137292 Издательство: Wiley Рейтинг: Цена: 12355.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets "--
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