Автор: Vittinghoff Название: Regression Methods in Biostatistics ISBN: 0387202757 ISBN-13(EAN): 9780387202754 Издательство: Springer Рейтинг: Цена: 75420.00 T Наличие на складе: Поставка под заказ. Описание: An introduction to the multipredictor regression methods widely used in biostatistics. This book covers linear models for continuous outcomes; logistic models for binary outcomes; the Cox model for right-censored survival times; repeated-measures models for longitudinal and hierarchical outcomes; and linear models for counts and other outcomes.
Автор: Moodie Название: Linear Regression And Anova ISBN: 1439869510 ISBN-13(EAN): 9781439869512 Издательство: Taylor&Francis Рейтинг: Цена: 83690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Designed for researchers primarily interested in what their data are revealing, this book presents statistical methods without burdening readers with matrix algebra and calculus. The book shows how high resolution, publication-ready graphics associated with regression and ANOVA methods are produced with virtually no effort by the SAS user.
Автор: Chernov, Nikolai Название: Circular and Linear Regression ISBN: 143983590X ISBN-13(EAN): 9781439835906 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Нет в наличии.
Автор: Tan, Frans E.s. Jolani, Shahab Название: Applied linear regression for longitudinal data ISBN: 0367634317 ISBN-13(EAN): 9780367634315 Издательство: Taylor&Francis Рейтинг: Цена: 100030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas.
Автор: McGibney Название: Applied Linear Regression for Business Analytics with R ISBN: 303121479X ISBN-13(EAN): 9783031214790 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.
Автор: Weisberg Sanford Название: Applied Linear Regression ISBN: 1118386086 ISBN-13(EAN): 9781118386088 Издательство: Wiley Рейтинг: Цена: 125610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Providing a coherent set of basic methodology for applied linear regression without being encyclopedic, the fourth edition of Applied Linear Regression is thoroughly updated to help students master the theory and applications of linear regression modeling.
Автор: Hocking Ronald R Название: Methods and Applications of Linear Models ISBN: 1118329503 ISBN-13(EAN): 9781118329504 Издательство: Wiley Рейтинг: Цена: 134060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Praise for the Second Edition "An essential desktop reference book... it should definitely be on your bookshelf.
Автор: Montgomery Douglas C., Peck Elizabeth A., Vining G. Geoffrey Название: Solutions Manual to Accompany Introduction to Linear Regression Analysis ISBN: 1119578698 ISBN-13(EAN): 9781119578697 Издательство: Wiley Рейтинг: Цена: 26930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume is a guide for scholars, policymakers, attorneys, teachers, judges, and students interested in the theories, policies, and doctrines of copyright law. Featuring experts from around the world, the handbook offers a systematic, comparative study of copyright in major jurisdictions including the United States, the European Union, and China.
Автор: Olive David J. Название: Linear Regression ISBN: 3319856081 ISBN-13(EAN): 9783319856087 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduction.- Multiple Linear Regression.- Building an MLR Model.- WLS and Generalized Least Squares.- One Way Anova.- The K Way Anova Model.- Block Designs.- Orthogonal Designs.- More on Experimental Designs.- Multivariate Models.- Theory for Linear Models.- Multivariate Linear Regression.- GLMs and GAMs.- Stuff for Students.
Автор: Sengupta Debasis, Jammalamadaka S. Rao Название: Linear Models and Regression with R: An Integrated Approach ISBN: 9811229287 ISBN-13(EAN): 9789811229282 Издательство: World Scientific Publishing Рейтинг: Цена: 99010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices.
Автор: Eric Vittinghoff; David V. Glidden; Stephen C. Shi Название: Regression Methods in Biostatistics ISBN: 1489998543 ISBN-13(EAN): 9781489998545 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.
Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.
New to the Second Edition
Reorganized to focus on unbalanced data
Reworked balanced analyses using methods for unbalanced data
Introductions to nonparametric and lasso regression
Introductions to general additive and generalized additive models
Examination of homologous factors
Unbalanced split plot analyses
Extensions to generalized linear models
R, Minitab(R), and SAS code on the author's website
The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.
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