Regression with Linear Predictors, Per Kragh Andersen; Lene Theil Skovgaard
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 Рейтинг: Цена: 83690.00 T Наличие на складе: Невозможна поставка. 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: Fox John Название: Applied Regression Analysis and Generalized Linear Models ISBN: 1452205663 ISBN-13(EAN): 9781452205663 Издательство: Sage Publications Рейтинг: Цена: 166850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
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.
Название: Regression, ANOVA, and the General Linear Model ISBN: 1412997356 ISBN-13(EAN): 9781412997355 Издательство: Sage Publications Рейтинг: Цена: 140450.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The author demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use
Автор: Sanford Weisberg Название: Applied Linear Regression, 3rd Edition ISBN: 0471663794 ISBN-13(EAN): 9780471663799 Издательство: Wiley Рейтинг: 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.
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