Logistic regression with missing values in the covariates:
Gespeichert in:
1. Verfasser: | |
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Format: | Abschlussarbeit Buch |
Sprache: | English |
Veröffentlicht: |
New York, NY [u.a.]
Springer
1994
|
Schriftenreihe: | Lecture notes in statistics
86 |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | 138 S. |
ISBN: | 3540942637 0387942637 |
Internformat
MARC
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100 | 1 | |a Vach, Werner |e Verfasser |0 (DE-588)111242738 |4 aut | |
245 | 1 | 0 | |a Logistic regression with missing values in the covariates |c Werner Vach |
264 | 1 | |a New York, NY [u.a.] |b Springer |c 1994 | |
300 | |a 138 S. | ||
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337 | |b n |2 rdamedia | ||
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490 | 1 | |a Lecture notes in statistics |v 86 | |
502 | |a Vollst. zugl.: Dortmund, Univ., Diss. | ||
650 | 4 | |a Analyse de régression | |
650 | 7 | |a Analyse de régression |2 ram | |
650 | 4 | |a Estimation, Théorie de l' | |
650 | 7 | |a Estimation, théorie de l' |2 ram | |
650 | 4 | |a Observations manquantes (Statistique) | |
650 | 7 | |a Observations manquantes (Statistique) |2 ram | |
650 | 7 | |a Regressieanalyse |2 gtt | |
650 | 7 | |a Schattingstheorie |2 gtt | |
650 | 4 | |a Estimation theory | |
650 | 4 | |a Missing observations (Statistics) | |
650 | 4 | |a Regression analysis | |
650 | 0 | 7 | |a Regressionsanalyse |0 (DE-588)4129903-6 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Schätztheorie |0 (DE-588)4121608-8 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
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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
|
any_adam_object | 1 |
author | Vach, Werner |
author_GND | (DE-588)111242738 |
author_facet | Vach, Werner |
author_role | aut |
author_sort | Vach, Werner |
author_variant | w v wv |
building | Verbundindex |
bvnumber | BV009252544 |
callnumber-first | Q - Science |
callnumber-label | QA278 |
callnumber-raw | QA278.2 |
callnumber-search | QA278.2 |
callnumber-sort | QA 3278.2 |
callnumber-subject | QA - Mathematics |
classification_rvk | QH 230 QH 234 SI 856 SK 840 |
ctrlnum | (OCoLC)29791911 (DE-599)BVBBV009252544 |
dewey-full | 519.5/36 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5/36 |
dewey-search | 519.5/36 |
dewey-sort | 3519.5 236 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik Wirtschaftswissenschaften |
format | Thesis Book |
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genre_facet | Hochschulschrift |
id | DE-604.BV009252544 |
illustrated | Not Illustrated |
indexdate | 2024-07-09T17:33:57Z |
institution | BVB |
isbn | 3540942637 0387942637 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-006157773 |
oclc_num | 29791911 |
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spelling | Vach, Werner Verfasser (DE-588)111242738 aut Logistic regression with missing values in the covariates Werner Vach New York, NY [u.a.] Springer 1994 138 S. txt rdacontent n rdamedia nc rdacarrier Lecture notes in statistics 86 Vollst. zugl.: Dortmund, Univ., Diss. 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 rswk-swf Schätztheorie (DE-588)4121608-8 gnd rswk-swf Logistische Verteilung (DE-588)4299453-6 gnd rswk-swf Fehlende Daten (DE-588)4264715-0 gnd rswk-swf Unvollkommene Information (DE-588)4140474-9 gnd rswk-swf Regressionsmodell (DE-588)4127980-3 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Logistische Verteilung (DE-588)4299453-6 s Regressionsmodell (DE-588)4127980-3 s Fehlende Daten (DE-588)4264715-0 s DE-604 Regressionsanalyse (DE-588)4129903-6 s Schätztheorie (DE-588)4121608-8 s Unvollkommene Information (DE-588)4140474-9 s Lecture notes in statistics 86 (DE-604)BV002447846 86 SWB Datenaustausch application/pdf 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 Inhaltsverzeichnis |
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 |
subject_GND | (DE-588)4129903-6 (DE-588)4121608-8 (DE-588)4299453-6 (DE-588)4264715-0 (DE-588)4140474-9 (DE-588)4127980-3 (DE-588)4113937-9 |
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 |
url | 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 |
volume_link | (DE-604)BV002447846 |
work_keys_str_mv | AT vachwerner logisticregressionwithmissingvaluesinthecovariates |