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Statistical methods for clinical studies in the presence of surrogate end points
Author(s) -
Leung Denis HengYan
Publication year - 2001
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/1467-985x.00215
Subject(s) - end point , strengths and weaknesses , surrogate endpoint , computer science , point (geometry) , risk analysis (engineering) , data science , management science , medicine , psychology , mathematics , engineering , pathology , social psychology , geometry , real time computing
The use of surrogate end points has become increasingly common in medical and biological research. This is primarily because, in many studies, the primary end point of interest is too expensive or too difficult to obtain. There is now a large volume of statistical methods for analysing studies with surrogate end point data. However, to our knowledge, there has not been a comprehensive review of these methods to date. This paper reviews some existing methods and summarizes the strengths and weaknesses of each method. It also discusses the assumptions that are made by each method and critiques how likely these assumptions are met in practice.