The Resource Applied logistic regression
Applied logistic regression
Resource Information
The item Applied logistic regression represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 2 library branches.
Resource Information
The item Applied logistic regression represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 2 library branches.
 Summary

 "A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis 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 stateoftheart 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 realworld 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 musthave 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"
 "This Third Edition continues to focus on applications and interpretation of results from fitting regression models to categorical response variables"
 Language
 eng
 Edition

 Third edition /
 David W. Hosmer, Jr., PhD, Stanley Lemeshow, PhD, Rodney X. Sturdivant, PhD.
 Extent
 1 online resource
 Contents

 Applied Logistic Regression; Contents; Preface to the Third Edition; 1 Introduction to the Logistic Regression Model; 1.1 Introduction; 1.2 Fitting the Logistic Regression Model; 1.3 Testing for the Significance of the Coefficients; 1.4 Confidence Interval Estimation; 1.5 Other Estimation Methods; 1.6 Data Sets Used in Examples and Exercises; 1.6.1 The ICU Study; 1.6.2 The Low Birth Weight Study; 1.6.3 The Global Longitudinal Study of Osteoporosis in Women; 1.6.4 The Adolescent Placement Study; 1.6.5 The Burn Injury Study; 1.6.6 The Myopia Study; 1.6.7 The NHANES Study
 1.6.8 The Polypharmacy StudyExercises; 2 The Multiple Logistic Regression Model; 2.1 Introduction; 2.2 The Multiple Logistic Regression Model; 2.3 Fitting the Multiple Logistic Regression Model; 2.4 Testing for the Significance of the Model; 2.5 Confidence Interval Estimation; 2.6 Other Estimation Methods; Exercises; 3 Interpretation of the Fitted Logistic Regression Model; 3.1 Introduction; 3.2 Dichotomous Independent Variable; 3.3 Polychotomous Independent Variable; 3.4 Continuous Independent Variable; 3.5 Multivariable Models; 3.6 Presentation and Interpretation of the Fitted Values
 3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 x 2 TablesExercises; 4 ModelBuilding Strategies and Methods for Logistic Regression; 4.1 Introduction; 4.2 Purposeful Selection of Covariates; 4.2.1 Methods to Examine the Scale of a Continuous Covariate in the Logit; 4.2.2 Examples of Purposeful Selection; 4.3 Other Methods for Selecting Covariates; 4.3.1 Stepwise Selection of Covariates; 4.3.2 Best Subsets Logistic Regression; 4.3.3 Selecting Covariates and Checking their Scale Using Multivariable Fractional Polynomials; 4.4 Numerical Problems; Exercises
 5 Assessing the Fit of the Model5.1 Introduction; 5.2 Summary Measures of Goodness of Fit; 5.2.1 Pearson ChiSquare Statistic, Deviance, and SumofSquares; 5.2.2 The HosmerLemeshow Tests; 5.2.3 Classification Tables; 5.2.4 Area Under the Receiver Operating Characteristic Curve; 5.2.5 Other Summary Measures; 5.3 Logistic Regression Diagnostics; 5.4 Assessment of Fit via External Validation; 5.5 Interpretation and Presentation of the Results from a Fitted Logistic Regression Model; Exercises; 6 Application of Logistic Regression with Different Sampling Models; 6.1 Introduction
 6.2 Cohort Studies6.3 CaseControl Studies; 6.4 Fitting Logistic Regression Models to Data from Complex Sample Surveys; Exercises; 7 Logistic Regression for Matched CaseControl Studies; 7.1 Introduction; 7.2 Methods For Assessment of Fit in a 1M Matched Study; 7.3 An Example Using the Logistic Regression Model in a 11 Matched Study; 7.4 An Example Using the Logistic Regression Model in a 1M Matched Study; Exercises; 8 Logistic Regression Models for Multinomial and Ordinal Outcomes; 8.1 The Multinomial Logistic Regression Model
 8.1.1 Introduction to the Model and Estimation of Model Parameters
 Isbn
 9781118548356
 Label
 Applied logistic regression
 Title
 Applied logistic regression
 Language
 eng
 Summary

 "A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis 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 stateoftheart 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 realworld 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 musthave 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"
 "This Third Edition continues to focus on applications and interpretation of results from fitting regression models to categorical response variables"
 Assigning source

 Provided by publisher
 Provided by publisher
 Cataloging source
 DLC
 http://library.link/vocab/creatorName
 Hosmer, David W
 Dewey number
 519.5/36
 Index
 index present
 LC call number
 QA278.2
 Literary form
 non fiction
 Nature of contents

 dictionaries
 bibliography
 NLM call number
 Online Book
 http://library.link/vocab/relatedWorkOrContributorName

 Lemeshow, Stanley
 Sturdivant, Rodney X
 http://library.link/vocab/subjectName

 Regression analysis
 Logistic Models
 MATHEMATICS
 Regression analysis
 Label
 Applied logistic regression
 Bibliography note
 Includes bibliographical references and index
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 Applied Logistic Regression; Contents; Preface to the Third Edition; 1 Introduction to the Logistic Regression Model; 1.1 Introduction; 1.2 Fitting the Logistic Regression Model; 1.3 Testing for the Significance of the Coefficients; 1.4 Confidence Interval Estimation; 1.5 Other Estimation Methods; 1.6 Data Sets Used in Examples and Exercises; 1.6.1 The ICU Study; 1.6.2 The Low Birth Weight Study; 1.6.3 The Global Longitudinal Study of Osteoporosis in Women; 1.6.4 The Adolescent Placement Study; 1.6.5 The Burn Injury Study; 1.6.6 The Myopia Study; 1.6.7 The NHANES Study
 1.6.8 The Polypharmacy StudyExercises; 2 The Multiple Logistic Regression Model; 2.1 Introduction; 2.2 The Multiple Logistic Regression Model; 2.3 Fitting the Multiple Logistic Regression Model; 2.4 Testing for the Significance of the Model; 2.5 Confidence Interval Estimation; 2.6 Other Estimation Methods; Exercises; 3 Interpretation of the Fitted Logistic Regression Model; 3.1 Introduction; 3.2 Dichotomous Independent Variable; 3.3 Polychotomous Independent Variable; 3.4 Continuous Independent Variable; 3.5 Multivariable Models; 3.6 Presentation and Interpretation of the Fitted Values
 3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 x 2 TablesExercises; 4 ModelBuilding Strategies and Methods for Logistic Regression; 4.1 Introduction; 4.2 Purposeful Selection of Covariates; 4.2.1 Methods to Examine the Scale of a Continuous Covariate in the Logit; 4.2.2 Examples of Purposeful Selection; 4.3 Other Methods for Selecting Covariates; 4.3.1 Stepwise Selection of Covariates; 4.3.2 Best Subsets Logistic Regression; 4.3.3 Selecting Covariates and Checking their Scale Using Multivariable Fractional Polynomials; 4.4 Numerical Problems; Exercises
 5 Assessing the Fit of the Model5.1 Introduction; 5.2 Summary Measures of Goodness of Fit; 5.2.1 Pearson ChiSquare Statistic, Deviance, and SumofSquares; 5.2.2 The HosmerLemeshow Tests; 5.2.3 Classification Tables; 5.2.4 Area Under the Receiver Operating Characteristic Curve; 5.2.5 Other Summary Measures; 5.3 Logistic Regression Diagnostics; 5.4 Assessment of Fit via External Validation; 5.5 Interpretation and Presentation of the Results from a Fitted Logistic Regression Model; Exercises; 6 Application of Logistic Regression with Different Sampling Models; 6.1 Introduction
 6.2 Cohort Studies6.3 CaseControl Studies; 6.4 Fitting Logistic Regression Models to Data from Complex Sample Surveys; Exercises; 7 Logistic Regression for Matched CaseControl Studies; 7.1 Introduction; 7.2 Methods For Assessment of Fit in a 1M Matched Study; 7.3 An Example Using the Logistic Regression Model in a 11 Matched Study; 7.4 An Example Using the Logistic Regression Model in a 1M Matched Study; Exercises; 8 Logistic Regression Models for Multinomial and Ordinal Outcomes; 8.1 The Multinomial Logistic Regression Model
 8.1.1 Introduction to the Model and Estimation of Model Parameters
 Control code
 830124707
 Edition

 Third edition /
 David W. Hosmer, Jr., PhD, Stanley Lemeshow, PhD, Rodney X. Sturdivant, PhD.
 Extent
 1 online resource
 Form of item
 online
 Isbn
 9781118548356
 Lccn
 2013010300
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 9781118548356
 http://library.link/vocab/ext/overdrive/overdriveId

 cl0500000291
 46db4358aa7846c98f7e43bf7b650ff5
 Specific material designation
 remote
 System control number
 (OCoLC)830124707
 Label
 Applied logistic regression
 Bibliography note
 Includes bibliographical references and index
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 Applied Logistic Regression; Contents; Preface to the Third Edition; 1 Introduction to the Logistic Regression Model; 1.1 Introduction; 1.2 Fitting the Logistic Regression Model; 1.3 Testing for the Significance of the Coefficients; 1.4 Confidence Interval Estimation; 1.5 Other Estimation Methods; 1.6 Data Sets Used in Examples and Exercises; 1.6.1 The ICU Study; 1.6.2 The Low Birth Weight Study; 1.6.3 The Global Longitudinal Study of Osteoporosis in Women; 1.6.4 The Adolescent Placement Study; 1.6.5 The Burn Injury Study; 1.6.6 The Myopia Study; 1.6.7 The NHANES Study
 1.6.8 The Polypharmacy StudyExercises; 2 The Multiple Logistic Regression Model; 2.1 Introduction; 2.2 The Multiple Logistic Regression Model; 2.3 Fitting the Multiple Logistic Regression Model; 2.4 Testing for the Significance of the Model; 2.5 Confidence Interval Estimation; 2.6 Other Estimation Methods; Exercises; 3 Interpretation of the Fitted Logistic Regression Model; 3.1 Introduction; 3.2 Dichotomous Independent Variable; 3.3 Polychotomous Independent Variable; 3.4 Continuous Independent Variable; 3.5 Multivariable Models; 3.6 Presentation and Interpretation of the Fitted Values
 3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 x 2 TablesExercises; 4 ModelBuilding Strategies and Methods for Logistic Regression; 4.1 Introduction; 4.2 Purposeful Selection of Covariates; 4.2.1 Methods to Examine the Scale of a Continuous Covariate in the Logit; 4.2.2 Examples of Purposeful Selection; 4.3 Other Methods for Selecting Covariates; 4.3.1 Stepwise Selection of Covariates; 4.3.2 Best Subsets Logistic Regression; 4.3.3 Selecting Covariates and Checking their Scale Using Multivariable Fractional Polynomials; 4.4 Numerical Problems; Exercises
 5 Assessing the Fit of the Model5.1 Introduction; 5.2 Summary Measures of Goodness of Fit; 5.2.1 Pearson ChiSquare Statistic, Deviance, and SumofSquares; 5.2.2 The HosmerLemeshow Tests; 5.2.3 Classification Tables; 5.2.4 Area Under the Receiver Operating Characteristic Curve; 5.2.5 Other Summary Measures; 5.3 Logistic Regression Diagnostics; 5.4 Assessment of Fit via External Validation; 5.5 Interpretation and Presentation of the Results from a Fitted Logistic Regression Model; Exercises; 6 Application of Logistic Regression with Different Sampling Models; 6.1 Introduction
 6.2 Cohort Studies6.3 CaseControl Studies; 6.4 Fitting Logistic Regression Models to Data from Complex Sample Surveys; Exercises; 7 Logistic Regression for Matched CaseControl Studies; 7.1 Introduction; 7.2 Methods For Assessment of Fit in a 1M Matched Study; 7.3 An Example Using the Logistic Regression Model in a 11 Matched Study; 7.4 An Example Using the Logistic Regression Model in a 1M Matched Study; Exercises; 8 Logistic Regression Models for Multinomial and Ordinal Outcomes; 8.1 The Multinomial Logistic Regression Model
 8.1.1 Introduction to the Model and Estimation of Model Parameters
 Control code
 830124707
 Edition

 Third edition /
 David W. Hosmer, Jr., PhD, Stanley Lemeshow, PhD, Rodney X. Sturdivant, PhD.
 Extent
 1 online resource
 Form of item
 online
 Isbn
 9781118548356
 Lccn
 2013010300
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 9781118548356
 http://library.link/vocab/ext/overdrive/overdriveId

 cl0500000291
 46db4358aa7846c98f7e43bf7b650ff5
 Specific material designation
 remote
 System control number
 (OCoLC)830124707
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