Availability: Logistic regression with missing values in the covariates

Logistic regression with missing values in the covariates:

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Bibliographic Details
Main Author:	Vach, Werner (Author)
Format:	Thesis/Dissertation Book
Language:	English
Published:	New York, NY [u.a.] Springer 1994
Series:	Lecture notes in statistics 86
Subjects:	Analyse de régression Estimation, Théorie de l' Estimation, théorie de l' Observations manquantes (Statistique) Regressieanalyse Schattingstheorie Estimation theory Missing observations (Statistics) Regression analysis Regressionsanalyse Schätztheorie Logistische Verteilung Fehlende Daten Unvollkommene Information Regressionsmodell Hochschulschrift
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006157773&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Physical Description:	138 S.
ISBN:	3540942637 0387942637

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Record in the Search Index

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adam_text	IMAGE 1 CONTENTS 1. INTRODUCTION 1 PART I: LOGISTIC REGRESSION WITH TWO CATEGORICAL COVARIATES 2. THE COMPLETE DATA CASE 4 3. MISSING VALUE MECHANISMS 6 4. ESTIMATION METHODS 8 4.1 MAXIMUM LIKELIHOOD (ML) ESTIMATION 4.2 PSEUDO MAXIMUM LIKELIHOOD (PML) ESTIMATION 4.3 THE FILLING METHOD 4.4 COMPLETE CASE ANALYSIS 4.5 ADDITIONAL CATEGORY 4.6 PROBABILITY IMPUTATION 4.7 OMISSION OF COVARIATE 5. QUANTITATIVE COMPARISONS: ASYMPTOTIC RESULTS 26 5.1 ASYMPTOTIC RELATIVE EFFICIENCY: ML ESTIMATION VS. PML ESTIMATION 5.2 ASYMPTOTIC RELATIVE EFFICIENCY: ML ESTIMATION VS. FILLING 5.3 ASYMPTOTIC RELATIVE EFFICIENCY: PML ESTIMATION VS. FILLING 5.4 ASYMPTOTIC RELATIVE EFFICIENCY: ML ESTIMATION VS. COMPLETE CASE ANALYSIS 5.5 ASYMPTOTIC RELATIVE EFFICIENCY: ML ESTIMATION FOR COMPLETE DATA VS. ML ESTIMATION FOR INCOMPLETE DATA 5.6 ASYMPTOTIC RELATIVE EFFICIENCY: ML ESTIMATION FOR COMPLETE DATA VS. COMPLETE CASE ANALYSIS 5.7 ASYMPTOTIC RELATIVE EFFICIENCY: A SUMMARY OF RESULTS 5.8 ASYMPTOTIC BIAS: COMPARISON OF PROBABILITY IMPUTATION, ADDITIONAL CATEGORY AND OMISSION OF COVARIATE 5.9 ASYMPTOTIC BIAS: EVALUATION OF CONDITIONAL PROBABILITY IMPUTATION 5.10 EVALUATING THE UNDERESTIMATION OF VARIANCE OF CONDITIONAL PROBABILITY IMPU- TATION 5.11 THE IMPORTANCE OF THE VARIANCE CORRECTION OF THE FILLING METHOD IMAGE 2 6. QUANTITATIVE COMPARISONS: RESULTS FROM FINITE SAMPLE SIZE SIMULATION STUDIES 61 6.1 FINITE BEHAVIOR OF ML ESTIMATION, PML ESTIMATION, FILLING AND COMPLETE CASE ANALYSIS 6.2 POWER COMPARISONS 6.3 EVALUATION OF CONDITIONAL PROBABILITY IMPUTATION 7. EXAMPLES 73 7.1 ILLUSTRATING ARTIFICIAL EXAMPLES 7.2 AN EXAMPLE WITH A REAL DATA SET 8. SENSITIVITY ANALYSIS 80 PART II: GENERALIZATIONS 9. GENERAL REGRESSION MODELS WITH MISSING VALUES IN ONE OF TWO COVARIATES 85 9.1 ML ESTIMATION 9.2 SEMIPARAMETRIC ML ESTIMATION 9.3 ESTIMATION OF THE SCORE FUNCTION 9.4 COMPLETE CASE ANALYSIS 9.5 MEAN IMPUTATION AND ADDITIONAL CATEGORY 9.6 THE COX PROPORTIONAL HAZARDS MODEL 10. GENERALIZATIONS FOR MORE THAN TWO COVARIATES 95 10.1 ONE COVARIATE WITH MISSING VALUES 10.2 MISSING VALUES IN MORE THAN ONE COVARIATE 11. MISSING VALUES AND SUBSAMPLING 98 11.1 TWO STAGE DESIGNS 11.2 SURROGATE COVARIATES AND VALIDATION SAMPLING 11.3 SUBSAMPLING OF THE NONRESPONDERS 11.4 (SUB-)SAMPLING OF ADDITIONAL VARIABLES 12. FURTHER EXAMPLES 103 12.1 EXAMPLE 1: RISK FACTORS FOR SUBSEQUENT CONTRALATERAL BREAST CANCER 12.2 EXAMPLE 2: A STUDY ON THE ROLE OF DNA CONTENT FOR THE PROGNOSIS OF OVARIAN CANCER PATIENTS IMAGE 3 13. DISCUSSION 112 13.1 STATISTICAL INFERENCE IF THE MAR ASSUMPTION IS SATISFIED 13.2 STATISTICAL INFERENCE IF THE MAR ASSUMPTION IS QUESTIONABLE 13.3 TOPICS OF FUTURE RESEARCH 13.4 FINAL REMARK A P P E N D I C ES 116 A.I ML ESTIMATION IN THE PRESENCE OF MISSING VALUES A.2 THE EM ALGORITHM B. 1 EXPLICIT REPRESENTATION OF THE SCORE FUNCTION OF ML ESTIMATION AND THE INFORMATION MATRIX IN THE COMPLETE DATA CASE B.2 EXPLICIT REPRESENTATION OF THE SCORE FUNCTION OF ML ESTIMATION AND THE INFORMATION MATRIX B.3 EXPLICIT REPRESENTATION OF THE QUANTITIES USED FOR THE ASYMPTOTIC VARIANCE OF THE PML ESTIMATES B.4 EXPLICIT REPRESENTATION OF THE QUANTITIES USED FOR THE ASYMPTOTIC VARIANCE OF THE ESTIMATES OF THE FILLING METHOD R E F E R E N C ES 131 NOTATION INDEX 136 SUBJECT INDEX 139
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spellingShingle	Vach, Werner Logistic regression with missing values in the covariates Lecture notes in statistics Analyse de régression Analyse de régression ram Estimation, Théorie de l' Estimation, théorie de l' ram Observations manquantes (Statistique) Observations manquantes (Statistique) ram Regressieanalyse gtt Schattingstheorie gtt Estimation theory Missing observations (Statistics) Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd Schätztheorie (DE-588)4121608-8 gnd Logistische Verteilung (DE-588)4299453-6 gnd Fehlende Daten (DE-588)4264715-0 gnd Unvollkommene Information (DE-588)4140474-9 gnd Regressionsmodell (DE-588)4127980-3 gnd
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title	Logistic regression with missing values in the covariates
title_auth	Logistic regression with missing values in the covariates
title_exact_search	Logistic regression with missing values in the covariates
title_full	Logistic regression with missing values in the covariates Werner Vach
title_fullStr	Logistic regression with missing values in the covariates Werner Vach
title_full_unstemmed	Logistic regression with missing values in the covariates Werner Vach
title_short	Logistic regression with missing values in the covariates
title_sort	logistic regression with missing values in the covariates
topic	Analyse de régression Analyse de régression ram Estimation, Théorie de l' Estimation, théorie de l' ram Observations manquantes (Statistique) Observations manquantes (Statistique) ram Regressieanalyse gtt Schattingstheorie gtt Estimation theory Missing observations (Statistics) Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd Schätztheorie (DE-588)4121608-8 gnd Logistische Verteilung (DE-588)4299453-6 gnd Fehlende Daten (DE-588)4264715-0 gnd Unvollkommene Information (DE-588)4140474-9 gnd Regressionsmodell (DE-588)4127980-3 gnd
topic_facet	Analyse de régression Estimation, Théorie de l' Estimation, théorie de l' Observations manquantes (Statistique) Regressieanalyse Schattingstheorie Estimation theory Missing observations (Statistics) Regression analysis Regressionsanalyse Schätztheorie Logistische Verteilung Fehlende Daten Unvollkommene Information Regressionsmodell Hochschulschrift
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work_keys_str_mv	AT vachwerner logisticregressionwithmissingvaluesinthecovariates

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