Linear Regression, Olive David J.

Автор: Darlington Richard B., Hayes Andrew F.
Название: Regression Analysis and Linear Models: Concepts, Applications, and Implementation
ISBN: 1462521134 ISBN-13(EAN): 9781462521135
Издательство: Taylor&Francis
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Цена: 83690.00 T
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Описание: Ephasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book`s examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable`s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.

Автор: Hocking Ronald R
Название: Methods and Applications of Linear Models
ISBN: 1118329503 ISBN-13(EAN): 9781118329504
Издательство: Wiley
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Цена: 134060.00 T
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Описание: Praise for the Second Edition "An essential desktop reference book... it should definitely be on your bookshelf.

Название: Regression Modeling Strategies
ISBN: 3319194240 ISBN-13(EAN): 9783319194240
Издательство: Springer
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Цена: 83850.00 T
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Описание: Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.

Автор: Olive, David.
Название: Linear regression /
ISBN: 3319552503 ISBN-13(EAN): 9783319552507
Издательство: Springer
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Цена: 83850.00 T
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Описание:

This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models.

This text is for graduates and undergraduates with a strong mathematical background. The prerequisites for this text are linear algebra and a calculus based course in statistics.

Автор: W. Kraemer; H. Sonnberger
Название: The Linear Regression Model Under Test
ISBN: 3642958788 ISBN-13(EAN): 9783642958786
Издательство: Springer
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Цена: 102480.00 T
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Описание: Similar credits are due to Adrian Pagan, Roberto Mariano and Garry Phillips, the econometrics guest professors at the Institute in the 1982 - 1984 period, who through their lectures and advice have contributed greatly to our effort.

Автор: Hoffmann John P.
Название: Linear Regression Models: Applications in R
ISBN: 0367753685 ISBN-13(EAN): 9780367753689
Издательство: Taylor&Francis
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Цена: 188850.00 T
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Описание: This book includes chapters on specifying the correct linear regression model, adjusting for measurement error, understanding the effects of influential observations, and using multilevel data.

Автор: Zelterman, Daniel (yale University, Connecticut)
Название: Regression for health and social science
ISBN: 1108478182 ISBN-13(EAN): 9781108478182
Издательство: Cambridge Academ
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Цена: 52790.00 T
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Описание: Using every-day examples and numerous exercises, this text covers the basics of linear models with a minimum of mathematics. The emphasis is on issues involved in the analysis and the interpretation of computer output. R code is provided and explained allowing readers to apply the methods to their own data.

Автор: Frank E. Harrell , Jr.
Название: Regression Modeling Strategies
ISBN: 331933039X ISBN-13(EAN): 9783319330396
Издательство: Springer
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Цена: 69870.00 T
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Описание: Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.

Автор: Per Kragh Andersen; Lene Theil Skovgaard
Название: Regression with Linear Predictors
ISBN: 1441971696 ISBN-13(EAN): 9781441971692
Издательство: Springer
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Цена: 74530.00 T
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Описание: This is a book about regression analysis, that is, the situation in statistics where the distribution of a response (or outcome) variable is related to - planatory variables (or covariates). This is an extremely common situation in the application of statistical methods in many ?elds, andlinear regression, - gistic regression, and Cox proportional hazards regression are frequently used for quantitative, binary, and survival time outcome variables, respectively. Several books on these topics have appeared and for that reason one may well ask why we embark on writing still another book on regression. We have two main reasons for doing this: 1. First, we want to highlightsimilaritiesamonglinear, logistic, proportional hazards, andotherregressionmodelsthatincludealinearpredictor. These modelsareoftentreatedentirelyseparatelyintextsinspiteofthefactthat alloperationsonthemodelsdealingwiththelinearpredictorareprecisely the same, including handling of categorical and quantitative covariates, testing for linearity and studying interactions. 2. Second, we want to emphasize that, for any type of outcome variable, multiple regression models are composed of simple building blocks that areaddedtogetherinthelinearpredictor: thatis, t-tests, one-wayanalyses of variance and simple linear regressions for quantitative outcomes, 2 2, 2 (k+1) tables and simple logistic regressions for binary outcomes, and 2-and (k+1)-sample logrank testsand simple Cox regressionsfor survival data. Thishastwoconsequences. Allthesesimpleandwellknownmethods can be considered as special cases of the regression models. On the other hand, the e?ect of a single explanatory variable in a multiple regression model can be interpreted in a way similar to that obtained in the simple analysis, however, now valid only for the other explanatory variables in the model "held ?xed."

Автор: Frank E. Harrell
Название: Regression Modeling Strategies
ISBN: 1441929185 ISBN-13(EAN): 9781441929181
Издательство: Springer
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Цена: 83810.00 T
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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: Sanford Weisberg
Название: Applied Linear Regression, 3rd Edition
ISBN: 0471663794 ISBN-13(EAN): 9780471663799
Издательство: Wiley
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Цена: 95570.00 T
Наличие на складе: Поставка под заказ.
Описание: Applied Linear Regression, Third Edition is thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, this Third Edition stresses using graphical methods to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. This text is an excellent tool f learning how to use linear regression analysis techniques to solve and gain insight into real--life problems.

Автор: Fox John
Название: Applied Regression Analysis and Generalized Linear Models
ISBN: 1452205663 ISBN-13(EAN): 9781452205663
Издательство: Sage Publications
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Цена: 166850.00 T
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Описание: Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.