A false-discovery-rate-based loss framework for selection of interactions

Statistics in Medicine

Volumn 27, Issue 11, 2008, Pages 2004-2021

  Chen, Wei ^a   Ghosh, Debashis ^b   Raghunathan, Trivellore E ^b   Sargent, Daniel J ^c  

^a KARMANOS CANCER INSTITUTE   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c MAYO CLINIC   (United States)

Author keywords

Bayesian loss; FDR; Interaction; Markov chain; Model building

Indexed keywords

ANTINEOPLASTIC AGENT; B LYMPHOCYTE INDUCED MATURATION PROTEIN 1; CD150 ANTIGEN; CD38 ANTIGEN; FLUOROURACIL; INTERFERON REGULATORY FACTOR 4; IRINOTECAN; MACROPHAGE INFLAMMATORY PROTEIN 1ALPHA; OXALIPLATIN; PROTEIN BCL 2; PROTEIN BCL 6; PROTEIN P53;

ADVANCED CANCER; ANALYTIC METHOD; ARTICLE; B CELL LYMPHOMA; BAYES THEOREM; CANCER COMBINATION CHEMOTHERAPY; CANCER SURVIVAL; CLINICAL TRIAL; COLORECTAL CANCER; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DECISION THEORY; FALSE DISCOVERY RATE; FALSE NEGATIVE RESULT; GENE EXPRESSION PROFILING; HUMAN; HYPOTHESIS; LARGE CELL LYMPHOMA; LINEAR REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MATHEMATICAL COMPUTING; MONTE CARLO METHOD; MULTIPLE REGRESSION; PHASE 3 CLINICAL TRIAL; PROGNOSIS; QUANTITATIVE ANALYSIS; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; SENSITIVITY ANALYSIS; SIMULATION;

ALGORITHMS; BAYES THEOREM; BIOMEDICAL RESEARCH; CLINICAL TRIALS, PHASE III AS TOPIC; COLORECTAL NEOPLASMS; CONFOUNDING FACTORS (EPIDEMIOLOGY); HUMANS; LYMPHOMA; MODELS, STATISTICAL; MONTE CARLO METHOD; OUTCOME ASSESSMENT (HEALTH CARE);

EID: 42949116898     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3118     Document Type: Article

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