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Nonparametric sequential monitoring of longitudinal trials
Author(s) -
Bogowicz P.,
Gombay E.,
Heo G.
Publication year - 2010
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4011
Subject(s) - nonparametric statistics , computer science , simple (philosophy) , mathematics , monte carlo method , statistics , longitudinal data , algorithm , data mining , philosophy , epistemology
This paper considers the sequential monitoring of multi‐armed longitudinal clinical trials. We describe an approach that is relatively simple and accessible. Sequential ranks are used to form partial sum statistics, yielding processes that have independent increments, and hence can be approximated by Brownian motions. Three monitoring procedures are proposed. The first two are asymptotic, continuous analogues of the well‐known Pocock and O'Brien–Fleming group sequential procedures, whereas the third procedure is exact. Performance of the procedures is assessed using Monte Carlo simulations. Data from an orthodontic clinical trial is used to illustrate the proposed methods, for the comparison of three treatment groups. Copyright © 2010 John Wiley & Sons, Ltd.