A surrogate-primary replacement algorithm for response-adaptive randomization in stroke clinical trials

Statistical Methods in Medical Research

Volumn 26, Issue 3, 2017, Pages 1078-1092

  Nowacki, Amy S ^a   Zhao, Wenle ^b   Palesch, Yuko Y ^b  

^a LERNER RESEARCH INSTITUTE   (United States)

^b MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

clinical trials; randomization; Response adaptive randomization; surrogate endpoints; unequal allocation

Indexed keywords

ALGORITHM; ARTICLE; CEREBROVASCULAR ACCIDENT; CLINICAL TRIAL (TOPIC); COMPUTER SIMULATION; HUMAN; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MAXIMUM LIKELIHOOD METHOD; OUTCOME ASSESSMENT; PROBABILITY; RANDOMIZATION; RESPONSE ADAPTIVE RANDOMIZATION; SAMPLE SIZE; STUDY DESIGN; SURROGATE PRIMARY REPLACEMENT ALGORITHM; PROCEDURES; RANDOMIZED CONTROLLED TRIAL (TOPIC); TREATMENT OUTCOME;

TISSUE PLASMINOGEN ACTIVATOR;

ALGORITHMS; COMPUTER SIMULATION; HUMANS; PROBABILITY; RANDOM ALLOCATION; RANDOMIZED CONTROLLED TRIALS AS TOPIC; STROKE; TISSUE PLASMINOGEN ACTIVATOR; TREATMENT OUTCOME;

EID: 85020748025     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280214567142     Document Type: Article

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