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020 _a9781118548356
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035 _a(OCoLC)830124707
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082 0 0 _a519.5/36
_223
084 _aMAT029030
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049 _aMAIN
100 1 _aHosmer, David W.
245 1 0 _aApplied logistic regression.
250 _aThird edition /
_bDavid W. Hosmer, Jr., PhD, Stanley Lemeshow, PhD, Rodney X. Sturdivant, PhD.
264 1 _aHoboken, New Jersey :
_bWiley,
_c[2013]
300 _a1 online resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aWiley series in probability and statistics
504 _aIncludes bibliographical references and index.
520 _a"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"--
_cProvided by publisher.
520 _a"This Third Edition continues to focus on applications and interpretation of results from fitting regression models to categorical response variables"--
_cProvided by publisher.
588 0 _aPrint version record and CIP data provided by publisher.
505 0 _aApplied 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.
505 8 _a1.6.8 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.
505 8 _a3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 x 2 TablesExercises; 4 Model-Building 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.
505 8 _a5 Assessing the Fit of the Model5.1 Introduction; 5.2 Summary Measures of Goodness of Fit; 5.2.1 Pearson Chi-Square Statistic, Deviance, and Sum-of-Squares; 5.2.2 The Hosmer-Lemeshow 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.
505 8 _a6.2 Cohort Studies6.3 Case-Control Studies; 6.4 Fitting Logistic Regression Models to Data from Complex Sample Surveys; Exercises; 7 Logistic Regression for Matched Case-Control Studies; 7.1 Introduction; 7.2 Methods For Assessment of Fit in a 1-M Matched Study; 7.3 An Example Using the Logistic Regression Model in a 1-1 Matched Study; 7.4 An Example Using the Logistic Regression Model in a 1-M Matched Study; Exercises; 8 Logistic Regression Models for Multinomial and Ordinal Outcomes; 8.1 The Multinomial Logistic Regression Model.
505 8 _a8.1.1 Introduction to the Model and Estimation of Model Parameters.
650 0 _aRegression analysis.
650 4 _aComputer adaptive testing.
650 4 _aLogistic regression.
650 4 _aRegression analysis.
650 7 _aMATHEMATICS
_xProbability & Statistics
_xRegression Analysis.
_2bisacsh
650 7 _aRegression analysis.
_2fast
_0(OCoLC)fst01432090
650 7 _aRegression analysis.
_2local
655 4 _aElectronic books.
700 1 _aLemeshow, Stanley.
700 1 _aSturdivant, Rodney X.
776 0 8 _iPrint version:
_aHosmer, David W.
_tApplied logistic regression.
_bThird edition.
_dHoboken, New Jersey : Wiley, [2013]
_z9780470582473
_w(DLC) 2013000403
_w(OCoLC)829999551
830 0 _aWiley series in probability and statistics.
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9781118548387
_zWiley Online Library [Free Download only for SUST IP]
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