Applied Logistic Regression

Applied Logistic Regression

From the reviews of the First Edition.

Author: David W. Hosmer, Jr.

Publisher: John Wiley & Sons

ISBN: 9780471654025

Category: Mathematics

Page: 392

View: 656

Categories: Mathematics

Applied Logistic Regression

Applied Logistic Regression

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and ...

Author: David W. Hosmer, Jr.

Publisher: John Wiley & Sons

ISBN: 9780470582473

Category: Mathematics

Page: 528

View: 221

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
Categories: Mathematics

Applied Logistic Regression Second Edition Book and Solutions Manual Set

Applied Logistic Regression  Second Edition  Book and Solutions Manual Set

From the reviews of the First Edition.

Author: David W. Hosmer, Jr.

Publisher: Wiley-Interscience

ISBN: 0471225894

Category: Mathematics

Page: 672

View: 565

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.
Categories: Mathematics

Applied Logistic Regression Analysis

Applied Logistic Regression Analysis

The focus in this Second Edition is on logistic regression models for individual level (but aggregate or grouped) data.

Author: Scott Menard

Publisher: SAGE

ISBN: 0761922083

Category: Mathematics

Page: 111

View: 105

The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
Categories: Mathematics

Applied Logistic Regression

Applied Logistic Regression

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and ...

Author: David W. Hosmer, Jr.

Publisher: John Wiley & Sons

ISBN: 9781118548394

Category: Mathematics

Page: 528

View: 538

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
Categories: Mathematics

Solutions Manual to accompany Applied Logistic Regression

Solutions Manual to accompany Applied Logistic Regression

Presenting information on logistic regression models, this work explains difficult concepts through illustrative examples. This is a solutions manual to accompany applied Logistic Regression, 2nd Edition.

Author: David W. Hosmer, Jr.

Publisher: Wiley-Interscience

ISBN: 0471208264

Category: Mathematics

Page: 280

View: 227

Presenting information on logistic regression models, this work explains difficult concepts through illustrative examples. This is a solutions manual to accompany applied Logistic Regression, 2nd Edition.
Categories: Mathematics

Applied Survival Analysis

Applied Survival Analysis

This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory.

Author: David W. Hosmer, Jr.

Publisher: John Wiley & Sons

ISBN: 9781118211588

Category: Mathematics

Page: 416

View: 184

THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.
Categories: Mathematics

Logistic Regression

Logistic Regression

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.

Author: Scott Menard

Publisher: SAGE

ISBN: 9781412974837

Category: Social Science

Page: 377

View: 509

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.
Categories: Social Science

Applied Ordinal Logistic Regression Using Stata

Applied Ordinal Logistic Regression Using Stata

The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from ...

Author: Xing Liu

Publisher: SAGE Publications

ISBN: 9781483319766

Category: Social Science

Page: 552

View: 368

The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Categories: Social Science

Applied Linear Regression

Applied Linear Regression

Master linear regression techniques with a new edition of a classic text Reviews of the Second Edition: "I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . ...

Author: Sanford Weisberg

Publisher: John Wiley & Sons

ISBN: 9781118625958

Category: Mathematics

Page:

View: 736

Categories: Mathematics

Logistic Regression Trees

Logistic Regression Trees

Non - parametric logistic and proportional odds regression , Applied Statistics 36
: 260 - 276 . Hastie , T . J . and Tibshirani , R . J . ( 1990 ) . Generalized Additive
Model , Chapman and Hall , London . Horowitz , E . and Sahni , S . ( 1984 ) .

Author: Lo Wen-Da

Publisher:

ISBN: WISC:89050003532

Category:

Page: 266

View: 624

Categories:

Quality Control and Applied Statistics

Quality Control and Applied Statistics

Interpreting parameters in logistic regression ; Inference for logistic regression ;
Logit models with categorical predictors ; Multiple logistic regression ; Fitting
logistic regression models ; Notes , Problems . 6. Building and Applying Logistic ...

Author:

Publisher:

ISBN: UOM:39076002155005

Category: Operations research

Page:

View: 823

Categories: Operations research

Introduction to Logistic Regression Models

Introduction to Logistic Regression Models

Freeman , D.H. , Jr. 1987. Applied categorical data analysis . Marcel Dekker ,
New York , N.Y. Gilchrist , W. 1984. Statistical modeling . John Wiley and Sons ,
Toronto , Ont . Hosmer , D.W. and S. Lemeshow . 1989. Applied logistic
regression .

Author: Wendy Anne Bergerud

Publisher:

ISBN: MINN:31951D01639810F

Category: Forest management

Page: 147

View: 909

Categories: Forest management

Methodology Application Document Logistic Regression Using the CODES Data

Methodology Application Document  Logistic Regression Using the CODES Data

6. Kleinbaum , D. G. and Kupper , L. L. Applied Regression Analysis and Other
Multivariable Methods . Belmont , CA : Wadsworth Publishing , 1978 . 7. Hosmer ,
D. W. , Jr. and Lemeshow , Stanley . Applied Logistic Regression .

Author: J. Walker

Publisher:

ISBN: UCBK:C100926942

Category: Brain

Page: 35

View: 807

Categories: Brain

Applied Regression Modeling

Applied Regression Modeling

The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work. Praise for the First Edition "The attention to detail is impressive.

Author: Iain Pardoe

Publisher: John Wiley & Sons

ISBN: 9781118345047

Category: Mathematics

Page: 346

View: 246

Praise for the First Edition "The attention to detail is impressive. The book is very wellwritten and the author is extremely careful with his descriptions .. . the examples are wonderful." —The AmericanStatistician Fully revised to reflect the latest methodologies and emergingapplications, Applied Regression Modeling, Second Editioncontinues to highlight the benefits of statistical methods,specifically regression analysis and modeling, for understanding,analyzing, and interpreting multivariate data in business, science,and social science applications. The author utilizes a bounty of real-life examples, casestudies, illustrations, and graphics to introduce readers to theworld of regression analysis using various software packages,including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear andcareful writing style, the book introduces modeling extensions thatillustrate more advanced regression techniques, including logisticregression, Poisson regression, discrete choice models, multilevelmodels, and Bayesian modeling. In addition, the Second Edition features clarificationand expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated andadditional problems are included at the end of each chapter,allowing readers to test their comprehension of the presentedmaterial. In addition, a related website features the book'sdatasets, presentation slides, detailed statistical softwareinstructions, and learning resources including additional problemsand instructional videos. With an intuitive approach that is not heavy on mathematicaldetail, Applied Regression Modeling, Second Edition is anexcellent book for courses on statistical regression analysis atthe upper-undergraduate and graduate level. The book also serves asa valuable resource for professionals and researchers who utilizestatistical methods for decision-making in their everyday work.
Categories: Mathematics

Best Practices in Logistic Regression

Best Practices in Logistic Regression

The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression.

Author: Jason W. Osborne

Publisher: SAGE

ISBN: 9781452244792

Category: Mathematics

Page: 488

View: 459

Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.
Categories: Mathematics

Forest Genetics

Forest Genetics

Such cases can be better identified by the use of logistic regression models . In
conclusion , it appears that the logistic regression analysis of morphological traits
has been successfully applied in this study , as a method of taxonomic ...

Author:

Publisher:

ISBN: MINN:31951P00755873O

Category: Forest genetics

Page:

View: 629

Categories: Forest genetics

Applied Mathematical Programming and Modeling IV APMOD 98

Applied Mathematical Programming and Modeling IV  APMOD 98

Empirical results In this section we discuss ( a ) overview of data and ( b )
comparison of the prediction results obtained by the logistic regression and by
the ANN models . ( a ) Overview of data Figure 8 shows the trend of the seven
significant ...

Author: Hercules Vladimirou

Publisher:

ISBN: STANFORD:36105110488066

Category: Computer programming

Page: 445

View: 588

Categories: Computer programming

Selecting Research Methods Methods for analysing and reporting results

Selecting Research Methods  Methods for analysing and reporting results

In contrast , stepwise logistic regression outputs only a single set of predictors ,
thus fostering the notion that the chosen model must be the best model . ... It is
hoped that researchers will begin to apply a more thoughtful approach to variable
selection in logistic regression instead of ... Applied logistic regression ( 2nd ed . )
.

Author: W. Paul Vogt

Publisher:

ISBN: NWU:35556038480323

Category: Social sciences

Page: 350

View: 453

Selecting Research Methods provides advice from prominent social scientists concerning the most crucial steps for planning and undertaking meaningful research: selecting the methods to be used. Contributors to the collection address methodological choices in four stages: design, sampling, coding and measurement, and analysis. The volumes provide an integrated approach to methodological choice in two ways. First, the contributions range from the early decisions about design options through the concluding choices about analyzing, interpreting, and presenting results. Second, the collection is integrated because it addresses the needs of projects that collect qualitative evidence, quantitative data, or both. Volume 1 concerns design choice; the articles focus on selecting designs that are effective for answering research questions and achieving the goals of the researcher. Volume 2 is on sampling and includes, in addition to sampling from populations, advice on choosing methods for recruiting informants for interviews, selecting sites for participant observation, and assigning subjects to control and experimental groups. Volume 3 reviews options for coding and measurement; it emphasizes methodological choices that enable researchers to study concepts in ways that enhance the reliability and validity of the research. Finally, the articles included in Volume 4 review the range of choices available among methods to analyze results and interpret the meanings of evidence
Categories: Social sciences