Applied Logistic Regression (3rd Edition)

所需积分/C币:50 2014-07-16 17:16:11 4.14MB PDF

逻辑回归经典之作,最新版本(3rd Edition)。排版非常精美,可以做标记及复制粘贴。
Applied Logistic regression Third Edition DAVID W. HOSMER. JR Professor of Biostatistics(Emeritus) Division of Biostatistics and Epidemiology Department of Public health School of public health and health sciences University of massachusetts Amherst Massachusetts STANLEY LEMESHOW College of Public Health Professor of biostatistics College of public health The Ohio State University Columbus. Ohio RODNEY X STURDIVANT Colonel, U.S. army Academy and associate professor Department of Mathematical Sciences United States Military Academy West point New york WILEY Copyright o 2013 by John Wiley Sons, Inc. All rights reserved Published by John Wiley Sons, InC, Hoboken, New Jersey. Published simultaneously in Callada No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as perinitted under Section 107 or 108 of the 1976 United States Copyright Acl, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clcarancc Centcr, Inc, 222 Rosewood Drivc, Danvcrs, MA 01923,(978)750-8400 fax(978)750-4470, should be addressed to the Permissions Department, John Wiley &Sons, Inc, Ill River Street Hoboken,NJ07030,(201)748-6011,fax(201)748-6008, or online at Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages For general information on our other products and services or for technical support, please contact ou Customer Care Department within the United States at (800)762-2974, outside the United States at (317)572-3993 or fax(317)572-4002 Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about wiley products. visit our web siteatwww.wileycom Library of Congress Cataloging-in-Publication Data Is available Hosmer. David w Applied Logistic Regression David w. Hosmer, Jr, Stanley Lemeshow, Rodney X. Sturdivant 3rd ed Includes bibliographic references and index ISBN9780-47058247-3 cloth) Printed in the united states of america 10987654321 To our wives, Trina, Elaine, and Mandy and our sons, daughters, and grandchildren Contents Preface to the third edition XIll 1 Introduction to the Logistic Regression Model 1.2 Fitting the Logistic Regression Model, 8 1.3 Testing for the Significance of the Coefficients, 10 1.4 Confidence interval estimation. 15 1.5 Other Estimation Methods. 20 1.6 Data Sets Used in Examples and exercises 22 1.6. 1 The ICU Study, 22 1.6.2 The Low Birth Weight Study, 24 1.6.3 The Global Longitudinal Study of Osteoporosis In 1. 6. 4 The Adolescent Placement Study, 26 1.6.5 The Burn Injury Study, 27 6.6 The Myopia Study, 20 1.6.7 The NhANES Study, 31 1.6.8 The Polypharmacy Study, 31 Exercises. 32 2 The Multiple logistic Regression Model 35 2.1 Introduction. 35 2.2 The Multiple logistic Regression Model, 35 2.3 Fitting the Multiple Logistic Regression Model, 37 2. 4 Testing for the significance of the model. 39 2.5 Confidence Interval estimat 2.6 Other estimation methods. 45 xercise CONTENTS 3 Interpretation of the Fitted Logistic Regression Model 49 3.1 Introduction. 49 3.2 Dichotomous Independent Variable, 50 3.3 Polychotomous Independent Variable, 56 3.4 Continuous Independent Variable, 62 3.5 Multivariable Models. 64 3.6 Presentation and Interpretation of the Fitted Values, 77 3.7 A Comparison of Logistic Regression and Stratified Analysis for2×2 Tables.82 Exercises. 87 4 Model-Building Strategies and Methods for Logistic Regression 4.1 Introduction. 89 4.2 Purposeful Selection of Covariates, 89 4.2.1 Methods to examine the scale of a continuous Covariate in the Logit. 94 4.2.2 Examples of Purposeful Selection, 107 4.3 Other Methods for Selecting Covariates, 124 4.3.1 Stepwise Selection of Covariates, 125 4.3.2 Best Subsets Logistic Regression, 133 4.3.3 Selecting Covariates and Checking their scale Using Multivariable Fractional Polynomials, 139 4. 4 Numerical Problems, 145 Exercises. 150 5 Assessing the fit of the model 153 5.1 Introduction. 153 5.2 Summary Measures of Goodness of Fit, 154 5.2.1 Pearson Chi-Square Statistic, Deviance and Sum-of-Squares, 155 5.2.2 The Hosmer-Lemeshow Tests. 157 5.2.3 Classification Tables. 169 5.2. 4 Area Under the Receiver Operating Characteristic Curve. 173 5.2.5 Other Summary Measures, 182 5.3 Logistic Regression diagnostics. 186 5.4 Assessment of fit via external validation 202 CONTENTS 5.5 Interpretation and Presentation of the Results from a Fitted Logistic regression Model, 212 Exercises. 223 6 Application of Logistic Regression with Different Sampling Models 7 6.1 Introduction. 227 2 Cohort Studies 227 6.3 Case-Control studies. 229 6. 4 Fitting Logistic regression Models to Data from Complex Sample surveys. 233 Exercises. 242 7 Logistic Regression for Matched Case-Control Studies 243 7.1 Introduction. 243 7.2 Methods For Assessment of fit in a 1-M Matched Study, 248 7.3 An Example Using the Logistic Regression Model in a 1-1 Matched Study 251 7.4 An Example Using the Logistic Regression Model in a 1-M Matched Study, 260 Exercises. 267 8 Logistic Regression Models for Multinomial and Ordinal Outcomes 269 8. 1 The Multinomial Logistic Regression Model, 269 8. 1.1 Introduction to the model and estimation of model Parameters. 269 8.1. 2 Interpreting and Assessing the Significance of the Estimated coeff 272 8.1.3 Model-Building Strategies for Multinomial logistic Regression. 278 8.1.4 Assessment of fit and diagnostic statistics for the Multinomial logistic Regression Model, 283 8.2 Ordinal logistic Regression models. 289 8.2.1 Introduction to the Models, Methods for Fitting, and Interpretation of Model Parameters, 289 8.2.2 Model Building Strategies for Ordinal Logistic Regression Models, 305 Exercises. 310 CONTENTS 9 Logistic Regression Models for the Analysis of Correlated Data 313 9.1 Introduction. 313 9.2 Logistic Regression Models for the Analysis of Correlated Data. 315 9.3 Estimation Methods for Correlated Data Logistic Regression Models. 318 9.4 Interpretation of Coefficients from Logistic Regression Models for the Analysis of Correlated Data, 323 9.4.1 Population Average Model, 324 9.4.2 Cluster-Specific Model, 326 9.4.3 Alternative Estimation Methods for the Cluster-Specific Model. 333 9.4.4 Comparison of Population Average and Cluster-Specific Model. 334 9.5 An Example of Logistic Regression Modeling with Correlated Data. 337 9.5.1 Choice of Model for Correlated Data Analysis, 338 9.5.2 Population Average Model. 339 9.5.3 Cluster-Specific Model. 344 9.5.4 Additional Points to Consider when Fitting Logistic Regression Models to Correlated Data, 351 9.6 Assessment of model fit 354 9.6.1 Assessment of Population Average model Fit, 354 9.6.2 Assessment of Cluster-Specific Model Fit, 365 9.6.3 Conclusions. 374 Exercises. 375 10 Special Topics 377 10.1 Introduction. 377 10.2 Application of Propensity Score Methods in Logistic Regression modeling, 377 10.3 Exact Methods for Logistic Regression Models, 387 10.4 Missing Data, 395 10.5 Sample Size Issues when Fitting Logistic Regression Models. 401 10.6 Bayesian Methods for Logistic Regression, 408 10.6.1 The Bayesian Logistic Regression Model, 410 10.6.2 MCMC Simulation. 411 CONTENTS 10.6.3 An Example of a Bayesian Analysis and Its Interpretation, 419 10.7 Other Link Functions for Binary Regression Models, 434 10.8 Mediation. 441 10.8.1 Distinguishing Mediators from Confounders, 441 10.8.2 Implications for the Interpretation of an Adjusted Logistic regression coefficient 443 10.8.3 Why Adjust for a Mediator?444 10.8.4 Using Logistic Regression to Assess Mediation Assumptions, 445 10.9 More about statistical interaction 448 10.9.1 Additive versus Multiplicative Scale-Risk Difference versus odds ratios. 448 10.9.2 Estimating and Testing Additive Interaction, 451 Exercises. 456 References 479

试读 127P Applied Logistic Regression (3rd Edition)

评论 下载该资源后可以进行评论 6

rakish2014 不错得教学参考书,考虑非独立数据问题,值得参考学习
心湛 很好的资源,非常感谢!
7386 很好的资源!
hxhxza2 学习逻辑回归不错的教科书。
herui1983 csdn已经有同名资源,但正如楼主所说,这个版本更新,文件支持复制
timeahead csdn已经有同名资源,但正如楼主所说,这个版本更新,文件支持复制

关注 私信 TA的资源

    Applied Logistic Regression (3rd Edition) 50积分/C币 立即下载
    Applied Logistic Regression (3rd Edition)第1页
    Applied Logistic Regression (3rd Edition)第2页
    Applied Logistic Regression (3rd Edition)第3页
    Applied Logistic Regression (3rd Edition)第4页
    Applied Logistic Regression (3rd Edition)第5页
    Applied Logistic Regression (3rd Edition)第6页
    Applied Logistic Regression (3rd Edition)第7页
    Applied Logistic Regression (3rd Edition)第8页
    Applied Logistic Regression (3rd Edition)第9页
    Applied Logistic Regression (3rd Edition)第10页
    Applied Logistic Regression (3rd Edition)第11页
    Applied Logistic Regression (3rd Edition)第12页
    Applied Logistic Regression (3rd Edition)第13页
    Applied Logistic Regression (3rd Edition)第14页
    Applied Logistic Regression (3rd Edition)第15页
    Applied Logistic Regression (3rd Edition)第16页
    Applied Logistic Regression (3rd Edition)第17页
    Applied Logistic Regression (3rd Edition)第18页
    Applied Logistic Regression (3rd Edition)第19页
    Applied Logistic Regression (3rd Edition)第20页


    50积分/C币 立即下载 >