Wiley, 2021. — 499 p. — ISBN 9781119715177. A thorough presentation of Quantile Regression designed to help readers obtain richer information from data analyses The conditional least-square or mean-regression (MR) analysis is the quantitative research method used to model and analyze the relationships between a dependent variable and one or more independent variables, where...
Springer, 2020. — 64 p. — (SpringerBriefs in Statistics - ABE). — ISBN: 978-3-030-57934-0, 978-3-030-57935-7. This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others – a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine....
2nd edition. — New York: Springer, 2021. — 471 p. Regression analysis of cause effect relationships is increasingly the core of medical and health research. This work is a 2nd edition of a 2017 pretty complete textbook and tutorial for students as well as recollection / update bench and help desk for professionals. It came to the authors' attention, that information of history,...
2nd edition. — Stata Press, 2021. — 732 p. — ISBN 978-1-59718-322-2. Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using...
Routledge, 2020. — 198 p. — ISBN: 978-1-138-33547-9. This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and...
CRC Press, 2020. — 514 p. — ISBN: 9780367458522. Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella -- namely, the conditional distribution model. It explains why the...
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