Accounting for Response Misclassification and Covariate Measurement Error Improves Power and Reduces Bias in Epidemiologic Studies

Annals of Epidemiology

Volumn 20, Issue 7, 2010, Pages 562-567

  Cheng, Dunlei ^a   Branscum, Adam J ^b   Stamey, James D ^c  

^a BAYLOR HEALTH CARE SYSTEM   (United States)

^b UNIVERSITY OF KENTUCKY   (United States)

^c BAYLOR UNIVERSITY   (United States)

Author keywords

Measurement Error; Power Calculations; Simulation

Indexed keywords

ACCOUNTING; ANALYTIC METHOD; ARTICLE; EPIDEMIOLOGY; MEASUREMENT ERROR; METHODOLOGY; MONTE CARLO METHOD; PRIORITY JOURNAL; REGRESSION ANALYSIS; RESPONSE VARIABLE; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIMULATION; STATISTICAL MODEL; SYSTEMATIC ERROR; COHORT ANALYSIS; CROSS-SECTIONAL STUDY; HUMAN; REPRODUCIBILITY; SELECTION BIAS; STANDARDS; STATISTICAL BIAS;

BIAS (EPIDEMIOLOGY); COHORT STUDIES; CROSS-SECTIONAL STUDIES; HUMANS; LOGISTIC MODELS; MODELS, STATISTICAL; MONTE CARLO METHOD; REPRODUCIBILITY OF RESULTS; RESEARCH DESIGN; SAMPLE SIZE; SELECTION BIAS;

EID: 77953556982     PISSN: 10472797     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.annepidem.2010.03.012     Document Type: Article

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