Hierarchical models for tumor xenograft experiments in drug development

Journal of Biopharmaceutical Statistics

Volumn 14, Issue 4, 2004, Pages 931-945

  Fang, Hong Bin ^a   Tian, Guo Liang ^a   Tan, Ming ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

Antitumor study; Bayesian hierarchical model; IBF sampler; Informative censoring; Mixed effects models; Restricted parameters; Truncation

Indexed keywords

IRINOTECAN; TEMOZOLOMIDE;

ANALYTIC METHOD; ANIMAL EXPERIMENT; ANIMAL MODEL; ANTINEOPLASTIC ACTIVITY; BAYES THEOREM; CANCER MODEL; CONTROLLED STUDY; DATA ANALYSIS; DRUG EFFICACY; DRUG RESPONSE; GROWTH RATE; INVERSE BAYES FORMULA SAMPLER; LONGITUDINAL STUDY; MAXIMUM LIKELIHOOD METHOD; MOUSE; NONHUMAN; NORMAL DISTRIBUTION; PRIORITY JOURNAL; REVIEW; TUMOR GROWTH; TUMOR XENOGRAFT;

ALGORITHMS; ANIMALS; ANTINEOPLASTIC AGENTS; ANTINEOPLASTIC AGENTS, PHYTOGENIC; ANTINEOPLASTIC COMBINED CHEMOTHERAPY PROTOCOLS; BAYES THEOREM; BRAIN NEOPLASMS; CAMPTOTHECIN; DACARBAZINE; HUMANS; LIKELIHOOD FUNCTIONS; LONGITUDINAL STUDIES; MARKOV CHAINS; MICE; MODELS, STATISTICAL; MONTE CARLO METHOD; NEOPLASM TRANSPLANTATION; NEUROBLASTOMA; PREDICTIVE VALUE OF TESTS; TRANSPLANTATION, HETEROLOGOUS;

EID: 9244242568     PISSN: 10543406     EISSN: None     Source Type: Journal    
DOI: 10.1081/BIP-200035462     Document Type: Review

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