A mixture model approach in gene-gene and gene-environmental interactions for binary phenotypes

Journal of Biopharmaceutical Statistics

Volumn 18, Issue 6, 2008, Pages 1150-1177

  Li, Lang ^a   Yu, Menggang ^a   Jason, Robarge D ^a   Shen, Changyu ^a   Azzouz, Faouzi ^a   McLeod, Howard L ^b   Borges Gonzales, Silvana ^a   Nguyen, Anne ^a   Skaar, Todd ^a   Desta, Zeruesenay ^a   Sweeney, Christopher J ^a   Flockhart, David A ^a  

^a INDIANA UNIVERSITY   (United States)

^b WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Gene gene interaction; Mixture model; Pharmacogenetics

Indexed keywords

ARTICLE; GENE INTERACTION; GENOTYPE; GENOTYPE ENVIRONMENT INTERACTION; PHENOTYPE; PRIORITY JOURNAL; REGRESSION ANALYSIS; SAMPLE SIZE; SIMULATION; STATISTICAL MODEL;

ALGORITHMS; ANTINEOPLASTIC AGENTS; BREAST NEOPLASMS; CLUSTER ANALYSIS; COMPUTER SIMULATION; ENVIRONMENT; FEMALE; GENE EXPRESSION REGULATION, NEOPLASTIC; GENOTYPE; HUMANS; LIKELIHOOD FUNCTIONS; LOGISTIC MODELS; MALE; MODELS, GENETIC; MODELS, STATISTICAL; MONTE CARLO METHOD; PHARMACOGENETICS; PHENOTYPE; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; TAMOXIFEN; TAXOIDS; TREATMENT OUTCOME;

EID: 57349087128     PISSN: 10543406     EISSN: 15205711     Source Type: Journal    
DOI: 10.1080/10543400802369038     Document Type: Article

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