Marginal structural models might overcome confounding when analyzing multiple treatment effects in observational studies

Journal of Clinical Epidemiology

Volumn 61, Issue 6, 2008, Pages 525-530

  Suarez, David ^a,b   Haro, Josep Maria ^a   Novick, Diego ^c   Ochoa, Susana ^a  

^a PARC SANITARI SANT JOAN DE DÉU   (Spain)

^b UNIVERSITY OF BARCELONA   (Spain)

^c ELI LILLY AND COMPANY   (United States)

Author keywords

Causality; Confounding; Marginal structural models; Observational studies; Pharmacoepidemiology; Treatment effectiveness

Indexed keywords

AMISULPRIDE; CLOZAPINE; NEUROLEPTIC AGENT; OLANZAPINE; QUETIAPINE; RISPERIDONE;

ADULT; CAUSAL MODELING; COMPARATIVE STUDY; CONFOUNDING VARIABLE; CONTROLLED STUDY; FEMALE; FOLLOW UP; HUMAN; MAJOR CLINICAL STUDY; MALE; OBSERVATIONAL STUDY; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; REMISSION; REVIEW; SCHIZOPHRENIA; STATISTICAL SIGNIFICANCE; TREATMENT OUTCOME;

ADULT; ANTIPSYCHOTIC AGENTS; CAUSALITY; CONFOUNDING FACTORS (EPIDEMIOLOGY); FEMALE; HUMANS; MALE; MODELS, STATISTICAL; REMISSION INDUCTION; SCHIZOPHRENIA; TREATMENT OUTCOME;

EID: 43049115395     PISSN: 08954356     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2007.11.007     Document Type: Review

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