Handbook Of Regression Methods


Handbook Of Regression Methods
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Handbook Of Regression Analysis


Handbook Of Regression Analysis
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Author : Samprit Chatterjee
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-30

Handbook Of Regression Analysis written by Samprit Chatterjee 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 2013-05-30 with Mathematics categories.


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. The focus is on the tools that both practitioners and researchers use in real life. It is intended to be a comprehensive collection of the theory, methods, and applications of regression methods, but it has been deliberately written at an accessible level. The handbook provides a quick and convenient reference or “refresher” on ideas and methods that are useful for the effective analysis of data and its resulting interpretations. Students can use the book as an introduction to and/or summary of key concepts in regression and related course work (including linear, binary logistic, multinomial logistic, count, and nonlinear regression models). Theory underlying the methodology is presented when it advances conceptual understanding and is always supplemented by hands-on examples. References are supplied for readers wanting more detailed material on the topics discussed in the book. R code and data for all of the analyses described in the book are available via an author-maintained website. "I enjoyed the presentation of the Handbook, and I would be happy to recommend this nice handy book as a reference to my students. The clarity of the writing and proper choices of examples allows the presentations ofmany statisticalmethods shine. The quality of the examples at the end of each chapter is a strength. They entail explanations of the resulting R outputs and successfully guide readers to interpret them." American Statistician



Handbook Of Regression Methods


Handbook Of Regression Methods
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Author : Derek Scott Young
language : en
Publisher: CRC Press
Release Date : 2018-10-03

Handbook Of Regression Methods written by Derek Scott Young and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Mathematics categories.


Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook provides a broad overview of regression models, diagnostic procedures, and inference procedures, with emphasis on how these methods are applied. The organization of the handbook benefits both practitioners and researchers, who seek either to obtain a quick understanding of regression methods for specialized problems or to expand their own breadth of knowledge of regression topics. This handbook covers classic material about simple linear regression and multiple linear regression, including assumptions, effective visualizations, and inference procedures. It presents an overview of advanced diagnostic tests, remedial strategies, and model selection procedures. Finally, many chapters are devoted to a diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression. Features Presents a concise overview of a wide range of regression topics not usually covered in a single text Includes over 80 examples using nearly 70 real datasets, with results obtained using R Offers a Shiny app containing all examples, thus allowing access to the source code and the ability to interact with the analyses



Handbook Of Regression Methods


Handbook Of Regression Methods
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Author : Derek Scott Young
language : en
Publisher: CRC Press
Release Date : 2018-10-03

Handbook Of Regression Methods written by Derek Scott Young and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Mathematics categories.


Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook provides a broad overview of regression models, diagnostic procedures, and inference procedures, with emphasis on how these methods are applied. The organization of the handbook benefits both practitioners and researchers, who seek either to obtain a quick understanding of regression methods for specialized problems or to expand their own breadth of knowledge of regression topics. This handbook covers classic material about simple linear regression and multiple linear regression, including assumptions, effective visualizations, and inference procedures. It presents an overview of advanced diagnostic tests, remedial strategies, and model selection procedures. Finally, many chapters are devoted to a diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression. Features Presents a concise overview of a wide range of regression topics not usually covered in a single text Includes over 80 examples using nearly 70 real datasets, with results obtained using R Offers a Shiny app containing all examples, thus allowing access to the source code and the ability to interact with the analyses



Handbook Of Regression Methods


Handbook Of Regression Methods
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Author : Derek S. Young
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2017

Handbook Of Regression Methods written by Derek S. Young and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Multivariate analysis categories.


This book provides a broad survey of both standard and nonstandard regression. Topics include those typically covered in a Master's-level statistics regression course- simple/multiple linear regression, residual analysis, ANOVA and specialized topics like biased regression procedures, multivariate regression, and count regression models.



The Sage Handbook Of Regression Analysis And Causal Inference


The Sage Handbook Of Regression Analysis And Causal Inference
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Author : Henning Best
language : en
Publisher: SAGE
Release Date : 2013-12-20

The Sage Handbook Of Regression Analysis And Causal Inference written by Henning Best and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-20 with Social Science categories.


′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.



Handbook Of Regression Modeling In People Analytics


Handbook Of Regression Modeling In People Analytics
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Author : Keith McNulty
language : en
Publisher: CRC Press
Release Date : 2021-07-29

Handbook Of Regression Modeling In People Analytics written by Keith McNulty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-29 with Business & Economics categories.


Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features: • 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) • Clear step-by-step instructions on executing the analyses. • Clear guidance on how to interpret results. • Primary instruction in R but added sections for Python coders. • Discussion exercises and data exercises for each of the main chapters. • Final chapter of practice material and datasets ideal for class homework or project work.



Handbook Of Regression Analysis With Applications In R


Handbook Of Regression Analysis With Applications In R
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Author : Samprit Chatterjee
language : en
Publisher: John Wiley & Sons
Release Date : 2020-07-30

Handbook Of Regression Analysis With Applications In R written by Samprit Chatterjee 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 2020-07-30 with Mathematics categories.


Handbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include: Regularization methods Smoothing methods Tree-based methods In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.



The Sage Handbook Of Regression Analysis And Causal Inference


The Sage Handbook Of Regression Analysis And Causal Inference
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Author : Henning Best
language : en
Publisher: SAGE
Release Date : 2014-09-27

The Sage Handbook Of Regression Analysis And Causal Inference written by Henning Best and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-27 with Reference categories.


'The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.' - John Fox, Professor, Department of Sociology, McMaster University 'The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.' - Ben Jann, Executive Director, Institute of Sociology, University of Bern 'Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.' -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.



The Sage Handbook Of Regression Analysis And Causal Inference


The Sage Handbook Of Regression Analysis And Causal Inference
DOWNLOAD

Author : Henning Best
language : en
Publisher:
Release Date :

The Sage Handbook Of Regression Analysis And Causal Inference written by Henning Best and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Causation categories.


Edited and written by a team of leading international social scientists, this handbook provides a comprehensive introduction to multivariate methods. It focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities.



Handbook Of Nonlinear Regression Models


Handbook Of Nonlinear Regression Models
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Author : David A. Ratkowsky
language : en
Publisher:
Release Date : 1990

Handbook Of Nonlinear Regression Models written by David A. Ratkowsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.


The background; An introduction to regression modeling; Nonlinear regression modeling; An illustrative example of regression modeling; The models; Models with one X variable, convex/concave curves; Models with one X variable, sigmoidally shaped curves; Models with one X variable, curves with maxima and minima; Models with more than one explanatory viariable; Other models and excluded models; Obtaining good initial parameter estimates; Summary; References; Table of symbols; Appendix; Author index; Subject index.