All your data are always missing: Incorporating bias due to measurement error into the potential outcomes framework

International Journal of Epidemiology

Volumn 44, Issue 4, 2015, Pages 1452-1459

  Edwards, Jessie K ^a   Cole, Stephen R ^a   Westreich, Daniel ^a  

^a University of North Carolina at Chapel Hill   (United States)

Author keywords

Bias (Epidemiology); Causal inference; HIV; Missing data

Indexed keywords

DISEASE TREATMENT; EPIDEMIOLOGY; ERROR ANALYSIS; HUMAN IMMUNODEFICIENCY VIRUS; UNCERTAINTY ANALYSIS;

ARTICLE; ASCERTAINMENT BIAS; CAUSAL ATTRIBUTION; CD4 LYMPHOCYTE COUNT; CONCEPTUAL FRAMEWORK; CONFOUNDING VARIABLE; DATA ANALYSIS; FOLLOW UP; HUMAN; MEASUREMENT ERROR; PRIORITY JOURNAL; PROBABILITY; SELECTION BIAS; UNCERTAINTY; METHODOLOGY; STANDARDS; STATISTICAL ANALYSIS; STATISTICAL BIAS; STATISTICAL MODEL;

BIAS (EPIDEMIOLOGY); DATA INTERPRETATION, STATISTICAL; MODELS, STATISTICAL; RESEARCH DESIGN;

EID: 84943766838     PISSN: 03005771     EISSN: 14643685     Source Type: Journal    
DOI: 10.1093/ije/dyu272     Document Type: Article

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