Applied Regression Analysis And Other Multivariable Methods
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Applied Regression Analysis And Other Multivariable Methods
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Author : Kleinbaum
language : en
Publisher:
Release Date : 1988-01-01
Applied Regression Analysis And Other Multivariable Methods written by Kleinbaum and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-01-01 with categories.
Applied Regression Analysis And Other Multivariable Methods
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Author : David G. Kleinbaum
language : en
Publisher: Duxbury
Release Date : 2008
Applied Regression Analysis And Other Multivariable Methods written by David G. Kleinbaum and has been published by Duxbury this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Multivariate analysis categories.
This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques.
Applied Regression Analysis And Other Multivariable Methods
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Author : David G. Kleinbaum
language : en
Publisher: Duxbury Resource Center
Release Date : 1988
Applied Regression Analysis And Other Multivariable Methods written by David G. Kleinbaum and has been published by Duxbury Resource Center this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Mathematics categories.
* An introductory text for undergraduates, graduates, and working professionals; emphasizes applications in public health, biology, and the social and behavioral sciences.
Applied Regression Analysis And Experimental Design
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Author : Richard J. Brook
language : en
Publisher: Routledge
Release Date : 2018-12-13
Applied Regression Analysis And Experimental Design written by Richard J. Brook and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-13 with Mathematics categories.
For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems. Stressing principles while keeping computational and theoretical details at a manageable level, Applied Regression Analysis and Experimental Design features an emphasis on vector geometry and least squares to unify and provide an intuitive basis for most topics covered... abundant examples and exercises using real-life data sets clearly illustrating practical of data analysis...essential exposure to MINITAB and GENSTAT computer packages , including computer printouts...and important background material such as vector and matrix properties and the distributional properties of quadratic forms. Designed to make theory work for students, this clearly written, easy-to-understand work serves as the ideal texts for courses Regression, Experimental Design, and Linear Models in a broad range of disciplines. Moreover, applied statisticians will find the book a useful reference for the general application of the linear model.
Applied Logistic Regression
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Author : David W. Hosmer, Jr.
language : en
Publisher: John Wiley & Sons
Release Date : 2004-10-28
Applied Logistic Regression written by David W. Hosmer, Jr. and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-10-28 with Mathematics categories.
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.
Multiple Regression And Beyond
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Author : Timothy Z. Keith
language : en
Publisher: Routledge
Release Date : 2019-01-14
Multiple Regression And Beyond written by Timothy Z. Keith and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-14 with Education categories.
Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This book: • Covers both MR and SEM, while explaining their relevance to one another • Includes path analysis, confirmatory factor analysis, and latent growth modeling • Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises • Extensive use of figures and tables providing examples and illustrating key concepts and techniques New to this edition: • New chapter on mediation, moderation, and common cause • New chapter on the analysis of interactions with latent variables and multilevel SEM • Expanded coverage of advanced SEM techniques in chapters 18 through 22 • International case studies and examples • Updated instructor and student online resources
Applied Linear Statistical Models
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Author : Michael H. Kutner
language : en
Publisher: McGraw-Hill Education
Release Date : 2005
Applied Linear Statistical Models written by Michael H. Kutner and has been published by McGraw-Hill Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Analysis of variance categories.
Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Logistic Regression
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Author : Scott W. Menard
language : en
Publisher: SAGE
Release Date : 2010
Logistic Regression written by Scott W. Menard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.
Multivariable Analysis
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Author : Mitchell H. Katz
language : en
Publisher: Cambridge University Press
Release Date : 2006-02-09
Multivariable Analysis written by Mitchell H. Katz and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-09 with Mathematics categories.
How to perform and interpret multivariable analysis, using plain language rather than complex derivations.
Multivariable Model Building
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Author : Patrick Royston
language : en
Publisher: John Wiley & Sons
Release Date : 2008-09-15
Multivariable Model Building written by Patrick Royston and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-15 with Mathematics categories.
Multivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed. This book proposes a systematic approach to building such models based on standard principles of statistical modeling. The main emphasis is on the fractional polynomial method for modeling the influence of continuous variables in a multivariable context, a topic for which there is no standard approach. Existing options range from very simple step functions to highly complex adaptive methods such as multivariate splines with many knots and penalisation. This new approach, developed in part by the authors over the last decade, is a compromise which promotes interpretable, comprehensible and transportable models.