Regression for health and social science, Zelterman, Daniel (yale University, Connecticut)
Автор: Hooshang Nayebi Название: Advanced Statistics for Testing Assumed Causal Relationships ISBN: 3030547531 ISBN-13(EAN): 9783030547530 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.
Автор: John Fox Название: Regression Diagnostics: An Introduction ISBN: 1544375220 ISBN-13(EAN): 9781544375229 Издательство: Sage Publications Рейтинг: Цена: 5859.00 р. Наличие на складе: Поставка под заказ.
Описание:
Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website at https://tinyurl.com/RegDiag.
Автор: Lewis-Beck Michael S. Professor, Lewis-Beck Colin Название: Applied Regression: An Introduction ISBN: 1483381471 ISBN-13(EAN): 9781483381473 Издательство: Sage Publications Рейтинг: Цена: 5859.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measures of tolerance and VIF within the discussion about collinearity.
Автор: Chatterjee Samprit Название: Handbook of Regression Analysis ISBN: 0470887168 ISBN-13(EAN): 9780470887165 Издательство: Wiley Рейтинг: Цена: 18842.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis. Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis.
Автор: Gordon, Rachel A. Название: Regression Analysis for the Social Sciences ISBN: 1138810533 ISBN-13(EAN): 9781138810532 Издательство: Taylor&Francis Рейтинг: Цена: 41342.00 р. Наличие на складе: Нет в наличии.
Автор: Onyiah, Leonard C. Название: Design and Analysis of Experiments ISBN: 1420060546 ISBN-13(EAN): 9781420060546 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Нет в наличии.
Автор: Borowiak, Dale S. Название: Model Discrimination for Nonlinear Regression Models ISBN: 0824780531 ISBN-13(EAN): 9780824780531 Издательство: Taylor&Francis Рейтинг: Цена: 38280.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Breiman, Leo Название: Classification and Regression Trees ISBN: 0412048418 ISBN-13(EAN): 9780412048418 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data.
Автор: Uusipaikka, Esa Название: Confidence Intervals in Generalized Regression Models ISBN: 0367387085 ISBN-13(EAN): 9780367387082 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Нет в наличии.
Описание:
A Cohesive Approach to Regression Models
Confidence Intervals in Generalized Regression Models introduces a unified representation--the generalized regression model (GRM)--of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data and its statistical model.
Provides a Large Collection of Models
The book encompasses a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox regression model. The author also explains methods of constructing confidence regions, profile likelihood-based confidence intervals, and likelihood ratio tests.
Uses Statistical Inference Package to Make Inferences on Real-Valued Parameter Functions
Offering software that helps with statistical analyses, this book focuses on producing statistical inferences for data modeled by GRMs. It contains numerical and graphical results while providing the code online.
Описание: Discusses the important theoretical concepts such as the Amortization System Constant, French System of Price Amortization, comparative analysis of these methods and American System of Amortization which provide a basic understanding of the correlation and regression analysis.
Автор: Ma, Xin Название: Using classification and regression trees ISBN: 1641132388 ISBN-13(EAN): 9781641132381 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14137.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Classification and regression trees (CART) is one of the several contemporary statistical techniques with good promise for research in many academic fields. There are very few books on CART, especially on applied CART.This book, as a good practical primer with a focus on applications, introduces the relatively new statistical technique of CART as a powerful analytical tool. The easy-to-understand (non-technical) language and illustrative graphs (tables) as well as the use of the popular statistical software program (SPSS) appeal to readers without strong statistical background. This book helps readers understand the foundation, the operation, and the interpretation of CART analysis, thus becoming knowledgeable consumers and skillful users of CART.The chapter on advanced CART procedures not yet well-discussed in the literature allows readers to effectively seek further empowerment of their research designs by extending the analytical power of CART to a whole new level. This highly practical book is specifically written for academic researchers, data analysts, and graduate students in many disciplines such as economics, social sciences, medical sciences, and sport sciences who do not have strong statistical background but still strive to take full advantage of CART as a powerful analytical tool for research in their fields.
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