Applied logistic regression. (Record no. 7294)

000 -LEADER
fixed length control field 09012nam a2200481 i 4500
001 - CONTROL NUMBER
EWU control number 7294
003 - CONTROL NUMBER IDENTIFIER
control field BD-DhEWU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20180128152109.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131226s2013 njua g b 001 0 eng d
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2013000403
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780470582473 (hardback)
International Standard Book Number 9781118514948 (oBook ISBN)
International Standard Book Number 9781118514924 (ePDF ISBN)
International Standard Book Number 9781118514931 (ePub ISBN)
International Standard Book Number 9781118514900 (eMOBI ISBN)
035 ## - SYSTEM CONTROL NUMBER
OCLC control number (OCoLC)843434502
-- (BD-DhEWU)7294
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Transcribing agency DLC
Description conventions rda
Modifying agency DLC
-- BD-DhEWU
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA278.2
Item number .H67 2013
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.536 HOA
Author mark and Year 2013
084 ## - OTHER CLASSIFICATION NUMBER
Classification number MAT029030
Source of number bisacsh
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Hosmer, David W.
9 (RLIN) 2708
245 10 - TITLE STATEMENT
Title Applied logistic regression.
250 ## - EDITION STATEMENT
Edition statement Third edition /
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 500 pages :
Other physical details illustrations ;
Dimensions 24 cm.
490 0# - SERIES STATEMENT
Series statement Wiley series in probability and statistics
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references (pages 459-478) and index.
505 ## - FORMATTED CONTENTS NOTE
Contents note Preface to the Third Edition xiii 1 Introduction to the Logistic Regression Model 1 1.1Introduction, 1 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 Women, 24 1.6.4 The Adolescent Placement Study, 26 1.6.5 The Burn Injury Study, 27 1.6.6 The Myopia Study, 29 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 Estimation, 42 2.6 Other Estimation Methods, 45 Exercises, 46 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 for 2 × 2 Tables, 82 Exercises, 87 4 Model-Building Strategies and Methods for Logistic Regression 89 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 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 227 6.1 Introduction, 227 6.2 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 Coefficients, 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 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 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 459 Index 479
520 ## - SUMMARY, ETC.
Summary, etc "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 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"--
Summary, etc "This Third Edition continues to focus on applications and interpretation of results from fitting regression models to categorical response variables"--
526 ## - STUDY PROGRAM INFORMATION NOTE
Program name Applied Statistics
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name Regression analysis.
9 (RLIN) 2220
Topical term or geographic name MATHEMATICS / Probability & Statistics / Regression Analysis
Source of heading or term bisacsh.
9 (RLIN) 2709
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lemeshow, Stanley.
9 (RLIN) 2710
Personal name Sturdivant, Rodney X.
9 (RLIN) 2711
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Online version:
Main entry heading Hosmer, David W.
Title Applied logistic regression.
Edition Third edition / David W. Hosmer, Jr., PhD, Stanley Lemeshow, PhD, Rodney X. Sturdivant, PhD.
Place, publisher, and date of publication Hoboken, New Jersey : Wiley, [2013]
International Standard Book Number 9781118548356
Record control number (DLC) 2013010300
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials Specified Cover image
Uniform Resource Identifier http://catalogimages.wiley.com/images/db/jimages/9780470582473.jpg
Materials Specified OCLC
Uniform Resource Identifier http://www.worldcat.org/title/applied-logistic-regression/oclc/843434502&referer=brief_results
Materials Specified E-book Fulltext
Uniform Resource Identifier http://lib.ewubd.edu/ebook/7294
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Text
Koha issues (borrowed), all copies 7
Holdings
Lost status Source of classification or shelving scheme Not for loan Collection code Permanent Location Current Location Shelving location Date of accession Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Date checked out Copy number Price effective from Koha item type
    Not For Loan Non-fiction EWU Library EWU Library Reserve Section 2013-12-26 Trim Education 10900.00 7 519.536 HOA 2013 25572 2017-04-17 2015-10-11 C-1 2013-12-28 Text
    Not For Loan Non-fiction EWU Library EWU Library Reserve Section 2015-05-13 Parama 8572.80   519.536 HOA 2013 26667 2015-05-28   C-2 2015-05-28 Text
      Non-fiction EWU Library EWU Library Circulation Section 2015-05-13 Parama 8572.80   519.536 HOA 2013 26668 2015-05-28   C-3 2015-05-28 Text
    Not For Loan Non-fiction EWU Library EWU Library E-book 2018-01-28       519.536 HOA 2013   2018-01-28     2018-01-28 E-Book

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