Multivariate statistics made simple: a practical approach
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boca Raton, FL
CRC Press
[2019]
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xvi, 242 Seiten Illustrationen, Diagramme |
| ISBN: | 9781138610958 |
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| adam_text | Contents Preface xi Authors xv 1 2 3 Multivariate Statistical Analysis—An Overview 1 1.1 An Appraisal of Statistical Analysis ....................................... 1.2 Structure of Multivariate Problems ....................................... 1.3 Univariate Data Description ................................................... 1.4 Standard Error (SE) and Confidence Interval (Cl) ............... 1.5 Multivariate Descriptive Statistics .......................................... 1.6 Covariance Matrix and Correlation Matrix ........................... 1.7 Data Visualization..................................................................... 1.8 The Multivariate Normal Distribution.................................... 1.9 Some Interesting Applications of Multivariate Analysis ... Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 1 4 7 7 8 14 16 23 25 26 27 29 Comparison of Multivariate Means 31 2.1 Multivariate Comparison of Mean Vectors.............................. 2.2 One-sample Hotelling’s T2 Test ............................................. 2.3 Confidence Intervals for Component Means........................... 2.4 Two-Sample Hotelling’s T2 Test ............................................. 2.5 Paired Comparison of Multivariate Mean Vectors ...............
Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 31 33 37 39 43 48 49 50 Analysis of Variance with Multiple Factors 51 3.1 Review of Univariate Analysis of Variance (ANOVA) .... 3.2 Multifactor ANOVA.................................................................. 3.3 ANOVA with a General Linear Model.................................... 3.4 Continuous Covariates and Adjustment ................................. 51 55 57 61
4 5 6 7 3.5 Non-Parametric Approach to ANOVA.................................... 3.6 Influence of Random Effects on ANOVA .............................. Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 65 68 69 69 71 Multivariate Analysis of Variance (MANOVA) 73 4.1 Simultaneous ANOVA of Several Outcome Variables............ 4.2 Test Procedure for MANOVA ................................................ 4.3 Interpreting the Output............................................................ 4.4 MANOVA with Age as a Covariate ....................................... 4.5 Using Age and BMI as Covariates .......................................... 4.6 Theoretical Model for Prediction............................................. Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 73 74 78 81 84 86 88 88 90 Analysis of Repeated Measures Data 91 5.1 Experiments with Repeated Measures.................................... 5.2 RM ANOVA Using SPSS ......................................................... 5.3 RM ANOVA Using MedCalc ................................................... 5.4 RM ANOVA with One
Grouping Factor................................. 5.5 Profile Analysis ........................................................................ Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 91 95 99 100 107 113 113 114 Multiple Linear Regression Analysis 115 6.1 The Concept of Regression ...................................................... 6.2 Multiple Linear Regression ...................................................... 6.3 Selection of Appropriate Variables into the Model ............... 6.4 Predicted Values from the Model............................................. 6.5 Quality of Residuals.................................................................. 6.6 Regression Model with Selected Records .............................. Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 115 118 120 126 128 129 131 131 134 Classification Problems in Medical Diagnosis 135 7.1 7.2 7.3 135 137 138 The Nature of Classification Problems.................................... Binary Classifiers and Evaluation of Outcomes..................... Performance Measures of Classifiers
.......................................
7.4 ROC Curve Analysis ............................................................... 7.5 Composite Classifiers ............................................................... 7.6 Biomarker Panels and Longitudinal Markers ........................ Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 8 Binary Classification with Linear Discriminant Analysis 8.1 The Problem of Discrimination................................................ 8.2 The Discriminant Score and Decision Rule ........................... 8.3 Understanding the Output ...................................................... 8.4 ROC Curve Analysis of Discriminant Score........................... 8.5 Extension of Binary Classification .......................................... Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 9 Logistic Regression for Binary Classification 9.1 9.2 9.3 9.4 Introduction .............................................................................. Simple Binary Logistic Regression .......................................... Binary Logistic Regression with Multiple Predictors............ Assessment
of the Model and Relative Effectiveness of Markers....................................................................................... 9.5 Logistic Regression with Interaction Terms ........................... Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 10 Survival Analysis and Cox Regression 10.1 Introduction .............................................................................. 10.2 Data Requirements for Survival Analysis .............................. 10.3 Estimation of Survival Time with Complete Data (No Censoring)........................................................................... 10.4 The Kaplan-Meier Method for Censored Data ..................... 10.5 Cox Regression Model............................................................... Summary........................................................... Do it yourself .................................................................................... Suggested Reading.............................................................................. 144 148 149 150 150 151 153 153 155 158 161 163 164 164 167 169 169 170 175 179 180 182 182 184 185 185 186 187 190 193 199 200 203
x Contents 11 Poisson Regression Analysis 11.1 Introduction .............................................................................. 11.2 General Form of Poisson Regression ....................................... 11.3 Selection of Variables and Subset Regression ........................ 11.4 Poisson Regression Using SPSS................................................ 11.5 Applications of the Poisson Regression model........................ Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. 12 Cluster Analysis and Its Applications 12.1 Data Complexity and the Need for Clustering ..................... 12.2 Measures of Similarity and General Approach to Clustering . 12.3 Hierarchical Clustering and Dendrograms.............................. 12.4 The Impact of Clustering Methods on the Results ............... 12.5 K-Means Clustering.................................................................. Summary............................................................................................. Do it yourself .................................................................................... Suggested Reading.............................................................................. Index 205 205 206 211 213 216 217 217 218 219 219 221 224 229 232 235 235 237 239
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| isbn | 9781138610958 |
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| spelling | Sarma, K. V. Verfasser (DE-588)170390012 aut Multivariate statistics made simple a practical approach K. V. S. Sarma, R. Vishnu Vardhan Boca Raton, FL CRC Press [2019] © 2019 xvi, 242 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 s DE-604 Vishnu Vardhan, R. Verfasser aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030890793&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Sarma, K. V. Vishnu Vardhan, R. Multivariate statistics made simple a practical approach Multivariate Analyse (DE-588)4040708-1 gnd |
| subject_GND | (DE-588)4040708-1 |
| title | Multivariate statistics made simple a practical approach |
| title_auth | Multivariate statistics made simple a practical approach |
| title_exact_search | Multivariate statistics made simple a practical approach |
| title_full | Multivariate statistics made simple a practical approach K. V. S. Sarma, R. Vishnu Vardhan |
| title_fullStr | Multivariate statistics made simple a practical approach K. V. S. Sarma, R. Vishnu Vardhan |
| title_full_unstemmed | Multivariate statistics made simple a practical approach K. V. S. Sarma, R. Vishnu Vardhan |
| title_short | Multivariate statistics made simple |
| title_sort | multivariate statistics made simple a practical approach |
| title_sub | a practical approach |
| topic | Multivariate Analyse (DE-588)4040708-1 gnd |
| topic_facet | Multivariate Analyse |
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