A Bayesian framework to account for uncertainty due to missing binary outcome data in pairwise meta-analysis

Statistics in Medicine

Volumn 34, Issue 12, 2015, Pages 2062-2080

  Turner, N L ^a   Dias, S ^a   Ades, A E ^a   Welton, N J ^a  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

Bayesian; Bias; Decision making; Meta analysis; Missing data; Pattern mixture model

Indexed keywords

ARTICLE; BAYES THEOREM; CALCULATION; CONTROLLED STUDY; DATA ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; OUTCOMES RESEARCH; PROBABILITY; STATISTICAL DISTRIBUTION; SYSTEMATIC ERROR; THERAPY EFFECT; DOSE RESPONSE; HUMAN; LITERATURE; META ANALYSIS (TOPIC); OUTCOME ASSESSMENT; PROCEDURES; RANDOMIZED CONTROLLED TRIAL (TOPIC); REPRODUCIBILITY; SCHIZOPHRENIA; STATISTICAL ANALYSIS; STATISTICAL BIAS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; UNCERTAINTY;

HALOPERIDOL; NEUROLEPTIC AGENT;

ANTIPSYCHOTIC AGENTS; BAYES THEOREM; BIAS (EPIDEMIOLOGY); DATA INTERPRETATION, STATISTICAL; DOSE-RESPONSE RELATIONSHIP, DRUG; HALOPERIDOL; HUMANS; META-ANALYSIS AS TOPIC; MODELS, STATISTICAL; OUTCOME ASSESSMENT (HEALTH CARE); RANDOMIZED CONTROLLED TRIALS AS TOPIC; REPRODUCIBILITY OF RESULTS; REVIEW LITERATURE AS TOPIC; SCHIZOPHRENIA; UNCERTAINTY;

EID: 84929241750     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6475     Document Type: Article

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