A simple G-computation algorithm to quantify the causal effect of a secondary illness on the progression of a chronic disease

Statistics in Medicine

Volumn 28, Issue 18, 2009, Pages 2325-2337

  van der Wal, W M ^a   Prins, M ^a,b   Lumbreras, B ^c   Geskus, R B ^a,b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b Health Service Amsterdam   (Netherlands)

^c MIGUEL HERNÁNDEZ UNIVERSITY   (Spain)

Author keywords

AIDS; Causal effect; G computation; HIV; Marginal structural models

Indexed keywords

ACQUIRED IMMUNE DEFICIENCY SYNDROME; ARTICLE; CALCULATION; CAUSAL MODELING; CD4 LYMPHOCYTE COUNT; CD4+ T LYMPHOCYTE; CHRONIC DISEASE; CONFIDENCE INTERVAL; CONFOUNDING VARIABLE; COVARIANCE; DISEASE COURSE; DISEASE MARKER; EXPOSURE VARIABLE; G COMPUTATION ALGORITHM; HAZARD RATIO; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MEASUREMENT ERROR; PROBABILITY; PROPORTIONAL HAZARDS MODEL; QUANTITATIVE ANALYSIS; SEROCONVERSION; STATISTICAL ANALYSIS; STATISTICAL MODEL; STRUCTURAL EQUATION MODELING; TUBERCULOSIS;

ACQUIRED IMMUNODEFICIENCY SYNDROME; AIDS-RELATED OPPORTUNISTIC INFECTIONS; ALGORITHMS; BIOMETRY; CD4 LYMPHOCYTE COUNT; CHRONIC DISEASE; COMPUTER SIMULATION; DISEASE PROGRESSION; HUMANS; PROPORTIONAL HAZARDS MODELS; RISK FACTORS; SUBSTANCE ABUSE, INTRAVENOUS; TUBERCULOSIS, PULMONARY;

EID: 69949103782     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3629     Document Type: Article

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