Applied Logistic Regression Analysis: Second Edition, Menard S
Старое издание
Автор: Heeringa Название: Applied Survey Data Analysis, Second Edition ISBN: 1498761607 ISBN-13(EAN): 9781498761604 Издательство: Taylor&Francis Рейтинг: Цена: 10311 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software.
Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book's updated Web site.
Автор: Rawlings Название: Applied Regression Analysis ISBN: 0387984542 ISBN-13(EAN): 9780387984544 Издательство: Springer Рейтинг: Цена: 11082 р. Наличие на складе: Поставка под заказ.
Описание: Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving
optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least
squares as an effective research tool.
"Applied Regression Analysis" is aimed at the
scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods
without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course
to graduate students.
"Applied Regression Analysis" serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It
also provides a bridge between a two-semester introduction to statistical methods and a theoretical linear models course. "Applied Regression Analysis" emphasizes the concepts and
the analysis of data sets.
It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting
regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models
are also discussed.
Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the
Internet.
Автор: Fox, Dr. John (mcmaster University, Hamilton, Onta Название: Applied regression analysis and generalized linear models ISBN: 0761930426 ISBN-13(EAN): 9780761930426 Издательство: Sage Publications Рейтинг: Цена: 8354 р. Наличие на складе: Поставка под заказ.
Описание: Gives coverage to regression models such as: generalized linear models; limited-dependent-variable-models; mixed models and Cox regression, among other methods.
Автор: Glantz Название: Primer Of Applied Regression & Analysis Of Variance ISBN: 0071824111 ISBN-13(EAN): 9780071824118 Издательство: McGraw-Hill Рейтинг: Цена: 15949 р. Наличие на складе: Невозможна поставка.
Описание: Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods.
Описание: With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources.New to This Edition Updated throughout to incorporate important developments in latent variable modeling. Chapter on Bayesian CFA and multilevel measurement models. Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. Utilizes the latest versions of major latent variable software packages.
Описание: Hamlet`s `To be or not to be` soliloquy is quoted more often than almost any other passage in Shakespeare. Part of the "Shakespeare Now!" series, this title takes this famous speech and looks at it`s meaning to reveal the questions and problems it raises. It reads the individual words, phrases and sentences of Hamlet`s speech in `slow motion`. Mixed modelling is one of the areas of statistical analysis that enables more powerful interpretation of data through the recognition of random effects. This book shows that mixed modelling is a natural extension of the more familiar statistical methods of regression analysis and analysis of variance. A guide to Spinoza`s masterpiece of Rationalist thought. It offers reader an unorthodox account of God, a novel version of the mind-body relation, a systematic theory of emotions and a prescription for human virtue and blessedness. It explains the philosophical background against which the book was written and the key themes inherent in the text.
Описание: The Second Edition has been rearranged and reorganized, as well as fully updated and expanded to cover new developments. Includes material on the AVE method and explains existing information in an even more user-friendly form. Includes additional exercises. Describes a general approach to the analysis of unbalanced mixed models Uses data-based approach to development and analysis. Data sets will be available on an FTP site
Автор: Benjamin Kedem Название: Regression Models for Time Series Analysis ISBN: 0471363553 ISBN-13(EAN): 9780471363552 Издательство: Wiley Рейтинг: Цена: 20488 р. Наличие на складе: Поставка под заказ.
Описание: Regression methods have been an integral part of time series analysis. Developments have made major strides in such areas as non continuous data where a linear model is not appropriate. This is a review of the regression methods in time series analysis.
Автор: George A. F. Seber Название: Linear Regression Analysis, 2nd Edition ISBN: 0471415405 ISBN-13(EAN): 9780471415404 Издательство: Wiley Рейтинг: Цена: 21581 р. Наличие на складе: Поставка под заказ.
Описание: Concise, mathematically clear, and comprehensive treatment of the subject. * Expanded coverage of diagnostics and methodsmodel fitting. * Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models. * More than 200 problems throughout the book plus outline solutions for the exercises. * This revision has been extensively class-tested.
Описание: There are many books that are excellent sources of knowledge about individual stastical tools (survival models, general linear models, etc.), but the art of data analysis is about choosing and using multiple tools. In the words of Chatfield "...students typically know the technical details of regressin for example, but not necessarily when and how to apply it. This argues the need for a better balance in the literature and in statistical teaching between techniques and problem solving strategies." Whether analyzing risk factors, adjusting for biases in observational studies, or developing predictive models, there are common problems that few regression texts address. For example, there are missing data in the majority of datasets one is likely to encounter (other than those used in textbooks!) but most regression texts do not include methods for dealing with such data effectively, and texts on missing data do not cover regression modeling.
Автор: David W. Hosmer Jr. Название: Applied Logistic Regression, 2nd Edition ISBN: 0471356328 ISBN-13(EAN): 9780471356325 Издательство: Wiley Рейтинг: Цена: 12994 р. Наличие на складе: Поставка под заказ.
Описание: Since the late 1960s the logistic regression (LR) model has become the standard method for regression analysis of dichotomous data in many fields, especially in the health sciences. This text offers an introduction to the LR model and examines its use in methods for modelling.
Автор: Hosmer, David W. Lemeshow, Stanley Название: Applied logistic regression textbook and solutions manual ISBN: 0471225894 ISBN-13(EAN): 9780471225898 Издательство: Wiley Рейтинг: Цена: 15538 р. Наличие на складе: Поставка под заказ.
Описание: Providing an introduction to the logistic regression model, this work includes software packages for the analysis of data sets. It contains discussion, from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers through the use of modeling techniques for dichotomous data in diverse fields.
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