Analysis of case-cohort designs with binary outcomes: Improving efficiency using whole-cohort auxiliary information

Statistical Methods in Medical Research

Volumn 26, Issue 2, 2017, Pages 691-706

  Noma, Hisashi ^a,b   Tanaka, Shiro ^c  

^a INSTITUTE OF STATISTICAL MATHEMATICS   (Japan)

^b GRADUATE UNIVERSITY FOR ADVANCED STUDIES   (Japan)

^c KYOTO UNIVERSITY   (Japan)

Author keywords

calibration estimator; multiple imputation; risk difference; risk ratio; semiparametric maximum likelihood; two phase designs; weighted estimating equation

Indexed keywords

ARTICLE; CASE CONTROL STUDY; CASE STUDY; COHORT ANALYSIS; HUMAN; LOGISTIC REGRESSION ANALYSIS; MULTIPLE IMPUTATION ESTIMATOR; NEPHROBLASTOMA; PROSPECTIVE STUDY; SEMIPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATOR; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL PARAMETERS; TWO-PHASE CASE-CONTROL STUDY; WEIGHTED ESTIMATOR; WHOLE COHORT AUXILIARY VARIABLE INFORMATION; BIOSTATISTICS; COMPUTER SIMULATION; KIDNEY TUMOR; PATHOLOGY; PROCEDURES; PROGNOSIS; STATISTICAL MODEL;

BIOSTATISTICS; CASE-CONTROL STUDIES; COHORT STUDIES; COMPUTER SIMULATION; HUMANS; KIDNEY NEOPLASMS; LIKELIHOOD FUNCTIONS; LOGISTIC MODELS; MODELS, STATISTICAL; PROGNOSIS; PROSPECTIVE STUDIES; WILMS TUMOR;

EID: 85018747207     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280214556175     Document Type: Article

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