Modelling count data with excessive zeros: The need for class prediction in zero-inflated models and the issue of data generation in choosing between zero-inflated and generic mixture models for dental caries data

Statistics in Medicine

Volumn 28, Issue 28, 2009, Pages 3539-3553

  Gilthorpe, Mark S ^a   Frydenberg, Morten ^b   Cheng, Yaping ^a   Baelum, Vibeke ^b,c  

^a UNIVERSITY OF LEEDS   (United Kingdom)

^b AARHUS UNIVERSITY   (Denmark)

^c AARHUS UNIVERSITY   (Denmark)

Author keywords

Dmft DMFT; Latent variable; Mixture modelling; Oral health; Zero inflated

Indexed keywords

ANALYSIS OF COVARIANCE; COMPUTER PREDICTION; CONFERENCE PAPER; CONTROLLED STUDY; DATA ANALYSIS; DATA SYNTHESIS; DENTAL CARIES; DISEASE COURSE; FEMALE; GENERIC MIXTURE MODEL; HUMAN; MALE; MATHEMATICAL MODEL; MEDICAL RESEARCH; ONSET AGE; OUTCOMES RESEARCH; RISK FACTOR; STATISTICAL DISTRIBUTION; STATISTICAL MODEL; STATISTICAL SIGNIFICANCE; ZERO INFLATED MODEL;

BAYES THEOREM; BRAZIL; CHILD; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DENTAL CARIES; DMF INDEX; HUMANS; INCIDENCE; MODELS, STATISTICAL; PREVALENCE;

EID: 70449704145     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3699     Document Type: Conference Paper

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