Applied regression analysis and other multivariable methods:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Pacific Grove
Duxbury Press
1998
|
| Ausgabe: | 3. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Bis 2. Aufl. u.d.T.: Kleinbaum, David G.: Applied regression analysis and multivariable methods |
| Beschreibung: | XVIII, 798 S. graph. Darst. 1 Diskette (12 cm) |
| ISBN: | 0534209106 |
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Datensatz im Suchindex
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| adam_text | Titel: Applied regression analysis and other multivariable methods
Autor: Kleinbaum, David G
Jahr: 1998
Contents 1-1 1-2 1-3 2-1 2-2 2-3 3-1 3-2 3-3 3-4 3-5 3-6 CONCEPTS AND EXAMPLES OF RESEARCH 1 Concepts 1 Examples 2 Concluding Remarks 5 References 6 CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS Classification of Variables 7 Overlapping of Classification Schemes 11 Choice of Analysis 11 References 13 BASIC STATISTICS: A REVIEW 14 Preview 14 Descriptive Statistics 15 Random Variables and Distributions 16 Sampling Distributions of t, % 2 , and F 19 Statistical Inference: Estimation 21 Statistical Inference: Hypothesis Testing 24
xii Contents 3-7 Error Rates, Power, and Sample Size 28 Problems 30 References 33 4-1 4-2 4-3 4-4 INTRODUCTION TO REGRESSION ANALYSIS Preview 34 Association versus Causality 35 Statistical versus Deterministic Models 37 Concluding Remarks 38 References 38 34 5 STRAIGHT-LINE REGRESSION ANALYSIS 39 5-1 Preview 39 5-2 Regression with a Single Independent Variable 39 5-3 Mathematical Properties of a Straight Line 42 5-4 Statistical Assumptions for a Straight-line Model 43 5-5 Determining the Best-fitting Straight Line 47 5-6 Measure of the Quality of the Straight-line Fit and Estimate of a 2 51 5-7 Inferences About the Slope and Intercept 52 5-8 Interpretations of Tests for Slope and Intercept 54 5-9 Inferences About the Regression Line ju Y x = fio + 57 5-10 Prediction of a New Value of Y at X 0 59 5-11 Assessing the Appropriateness of the Straight-line Model 60 Problems 60 References 87 s THE CORRELATION COEFFICIENT 0 AND STRAIGHT-LINE REGRESSION ANALYSIS 88 6-1 Definition of r 88 6-2 r as a Measure of Association 89 6-3 The Bivariate Normal Distribution 90 6-4 r and the Strength of the Straight-line Relationship 93 6-5 What r Does Not Measure 95 6-6 Tests of Hypotheses and Confidence Intervals for the Correlation Coefficient 6-7 Testing for the Equality of Two Correlations 99 Problems 101 References 103
Contents xiii THE ANALYSIS-OF-VARIANCE TABLE 104 7-1 Preview 104 7-2 The ANOVA Table for Straight-line Regression 104 Problems 108 g MULTIPLE REGRESSION ANALYSIS: 0 GENERAL CONSIDERATIONS 111 8-1 Preview 111 8-2 Multiple Regression Models 112 8-3 Graphical Look at the Problem 113 8-4 Assumptions of Multiple Regression 115 8-5 Determining the Best Estimate of the Multiple Regression Equation 118 8-6 The ANOVA Table for Multiple Regression 119 8-7 Numerical Examples 121 Problems 123 References 135 TESTING HYPOTHESES IN MULTIPLE REGRESSION 136 9-1 Preview 136 9-2 Test for Significant Overall Regression 137 9-3 Partial F Test 138 9-4 Multiple Partial F Test 143 9-5 Strategies for Using Partial F Tests 145 9-6 Tests Involving the Intercept 150 Problems 151 References 159 ? CORRELATIONS: MULTIPLE, PARTIAL, AND MULTIPLE PARTIAL 160 10-1 Preview 160 10-2 Correlation Matrix 161 10-3 Multiple Correlation Coefficient 162 10-4 Relationship of RY x h x 2 ,...,x k to the Multivariate Normal Distribution 164 10-5 Partial Correlation Coefficient 165 10-6 Alternative Representation of the Regression Model 172
Contents 10-7 Multiple Partial Correlation 172 10-8 Concluding Remarks 174 Problems 174 Reference 185 CONFOUNDING AND INTERACTION IN REGRESSION 11-1 Preview 186 11-2 Overview 186 11-3 Interaction in Regression 188 11-4 Confounding in Regression 194 11-5 Summary and Conclusions 199 Problems 199 Reference 211 llllll REGRESSION DIAGNOSTICS 212 12-1 Preview 212 12-2 Simple Approaches to Diagnosing Problems in Data 212 12-3 Residual Analysis 216 12-4 Treating Outliers 228 12-5 Collinearity 237 12-6 Scaling Problems 248 12-7 Treating Collinearity and Scaling Problems 248 12-8 Alternate Strategies of Analysis 249 12-9 An Important Caution 252 Problems 253 References 279 POLYNOMIAL REGRESSION 281 13-1 Preview 281 13-2 Polynomial Models 282 13-3 Least-squares Procedure for Fitting a Parabola 282 13-4 ANOVA Table for Second-order Polynomial Regression 284 13-5 Inferences Associated with Second-order Polynomial Regression 284 13-6 Example Requiring a Second-order Model 286 13-7 Fitting and Testing Higher-order Models 290 13-8 Lack-of-fit Tests 290 13-9 Orthogonal Polynomials 292
Contents xv 13-10 Strategies for Choosing a Polynomial Model 301 Problems 302 1 4 DUMMY VARIABLES IN REGRESSION 317 14-1 Preview 317 14-2 Definitions 317 14-3 Rule for Defining Dummy Variables 318 14-4 Comparing Two Straight-line Regression Equations: An Example 319 14-5 Questions for Comparing Two Straight Lines 320 14-6 Methods of Comparing Two Straight Lines 321 14-7 Method I: Using Separate Regression Fits to Compare Two Straight Lines 322 14-8 Method H: Using a Single Regression Equation to Compare Two Straight Lines 327 14-9 Comparison of Methods I and II 330 14-10 Testing Strategies and Interpretation: Comparing Two Straight Lines 330 14-11 Other Dummy Variable Models 332 14-12 Comparing Four Regression Equations 334 14-13 Comparing Several Regression Equations Involving Two Nominal Variables 336 Problems 338 References 360 ?j . ANALYSIS OF COVARIANCE AND OTHER A ^ METHODS FOR ADJUSTING CONTINUOUS DATA 361 15-1 Preview 361 15-2 Adjustment Problem 361 15-3 Analysis of Covariance 363 15-4 Assumption of Parallelism: A Potential Drawback 365 15-5 Analysis of Covariance: Several Groups and Several Covariates 366 15-6 Comments and Cautions 368 15-7 Summary 371 Problems 371 Reference 385 SELECTING THE BEST REGRESSION EQUATION 386 16-1 Preview 386 16-2 Steps in Selecting the Best Regression Equation 387 16-3 Step 1: Specifying the Maximum Model 387 16-4 Step 2: Specifying a Criterion for Selecting a Model 390 16-5 Step 3: Specifying a Strategy for Selecting Variables 392
xvi Contents 16-6 Step 4: Conducting the Analysis 401 16-7 Step 5: Evaluating Reliability with Split Samples 401 16-8 Example Analysis of Actual Data 403 16-9 Issues in Selecting the Most Valid Model 409 Problems 409 References 422 ONE-WAY ANALYSIS OF VARIANCE 423 17-1 Preview 423 17-2 One-way ANOVA: The Problem, Assumptions, and Data Configuration 426 17-3 Methodology for One-way Fixed-effects ANOVA 429 17-4 Regression Model for Fixed-effects One-way ANOVA 435 17-5 Fixed-effects Model for One-way ANOVA 438 17-6 Random-effects Model for One-way ANOVA 440 17-7 Multiple-comparison Procedures for Fixed-effects One-way ANOVA 443 17-8 Choosing a Multiple-comparison Technique 456 17-9 Orthogonal Contrasts and Partitioning an ANOVA Sum of Squares 457 Problems 463 References 483 RANDOMIZED BLOCKS: SPECIAL CASE OF TWO-WAY ANOVA 484 18-1 Preview 484 18-2 Equivalent Analysis of a Matched Pairs Experiment 488 18-3 Principle of Blocking 491 18-4 Analysis of a Randomized-blocks Experiment 493 18-5 ANOVA Table for a Randomized-blocks Experiment 495 18-6 Regression Models for a Randomized-blocks Experiment 499 18-7 Fixed-effects ANOVA Model for a Randomized-blocks Experiment 502 Problems 503 References 515 1 TWO-WAY ANOVA WITH EQUAL CELL NUMBERS 516 19-1 Preview 516 19-2 Using a Table of Cell Means 518 19-3 General Methodology 522 19-4 F Tests for Two-way ANOVA 527 19-5 Regression Model for Fixed-effects Two-way ANOVA 530 19-6 Interactions in Two-way ANOVA 534 19-7 Random- and Mixed-effects Two-way ANOVA Models 541 Problems 544 References 560
Contents xvii Essa TWO-WAY ANOVA WITH UNEQUAL CELL NUMBERS 561 20-1 Preview 561 20-2 Problems with Unequal Cell Numbers: Nonorthogonality 563 20-3 Regression Approach for Unequal Cell Sample Sizes 567 20-4 Higher-way ANOVA 571 Problems 572 References 588 ANALYSIS OF REPEATED MEASURES DATA 589 21-1 Preview 589 21-2 Examples 590 21-3 General Approach for Repeated Measures ANOVA 592 21-4 Overview of Selected Repeated Measures Designs and ANOVA-based Analyses 21-5 Repeated Measures ANOVA for Unbalanced Data 611 21-6 Other Approaches to Analyzing Repeated Measures Data 612 Appendix 21-A Examples of SAS’s GLM and MIXED Procedures 613 Problems 616 References 638 594 THE METHOD OF MAXIMUM LIKELIHOOD 639 22-1 Preview 639 22-2 The Principle of Maximum Likelihood 639 22-3 Statistical Inference via Maximum Likelihood 22-4 Summary 652 Problems 653 References 655 642 23 LOGISTIC REGRESSION ANALYSIS 656 23-1 Preview 656 23-2 The Logistic Model 656 23-3 Estimating the Odds Ratio Using Logistic Regression 23-4 A Numerical Example of Logistic Regression 664 23-5 Theoretical Considerations 671 23-6 An Example of Conditional ML Estimation Involving Pair-matched Data with Unmatched Covariates 23-7 Summary 681 Problems 682 References 686 658 677
xviii Contents jp|J|| POISSON REGRESSION ANALYSIS 687 24-1 Preview 687 24-2 The Poisson Distribution 687 24-3 An Example of Poisson Regression 688 24-4 Poisson Regression: General Considerations 690 24-5 Measures of Goodness of Fit 694 24-6 Continuation of Skin Cancer Data Example 696 24-7 A Second Illustration of Poisson Regression Analysis 701 24-8 Summary 704 Problems 705 References 709 A APPENDIX A—TABLES 711 A-l Standard Normal Cumulative Probabilities 712 A-2 Percentiles of the t Distribution 715 A-3 Percentiles of the Chi-square Distribution 716 A-4 Percentiles of the F Distribution 717 A-5 Values of i In 7 —— 724 1 — r A -6 Upper a Point of Studentized Range 726 A-7 Orthogonal Polynomial Coefficients 728 A -8 Bonferroni Corrected Jackknife and Studentized Residual Critical Values 729 A-9 Critical Values for Leverages 730 A-10 Critical Values for the Maximum of N Values of Cook’s d(i) times (n-k - 1) 731 T) APPENDIX B—MATRICES AND THEIR ß RELATIONSHIP TO REGRESSION ANALYSIS 732 n APPENDIX C—ANOVA INFORMATION FOR FOUR ^ COMMON BALANCED REPEATED MEASURES DESIGNS 744 C-1 Balanced Repeated Measures Design with One Crossover Factor (Treatments) 744 C-2 Balanced Repeated Measures Design with Two Crossover Factors 746 C-3 Balanced Repeated Measures Design with One Nest Factor (Treatments) 750 C-4 Balanced Repeated Measures Design with One Crossover Factor and One Nest Factor C-5 Balanced Two-group Pre/Posttest Design 755 References 757 D SOLUTIONS TO EXERCISES 758 INDEX 787
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| spelling | Applied regression analysis and other multivariable methods David G. Kleinbaum ... 3. ed. Pacific Grove Duxbury Press 1998 XVIII, 798 S. graph. Darst. 1 Diskette (12 cm) txt rdacontent n rdamedia nc rdacarrier Bis 2. Aufl. u.d.T.: Kleinbaum, David G.: Applied regression analysis and multivariable methods Multivariate analysis Regression analysis Methode (DE-588)4038971-6 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf 1\p (DE-588)4151278-9 Einführung gnd-content Regressionsanalyse (DE-588)4129903-6 s DE-604 Multivariate Analyse (DE-588)4040708-1 s Methode (DE-588)4038971-6 s 2\p DE-604 Kleinbaum, David G. 1941- Sonstige (DE-588)114206422 oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007851232&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
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| title | Applied regression analysis and other multivariable methods |
| title_auth | Applied regression analysis and other multivariable methods |
| title_exact_search | Applied regression analysis and other multivariable methods |
| title_full | Applied regression analysis and other multivariable methods David G. Kleinbaum ... |
| title_fullStr | Applied regression analysis and other multivariable methods David G. Kleinbaum ... |
| title_full_unstemmed | Applied regression analysis and other multivariable methods David G. Kleinbaum ... |
| title_short | Applied regression analysis and other multivariable methods |
| title_sort | applied regression analysis and other multivariable methods |
| topic | Multivariate analysis Regression analysis Methode (DE-588)4038971-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| topic_facet | Multivariate analysis Regression analysis Methode Multivariate Analyse Regressionsanalyse Einführung |
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