ADAPTIVE GROUP SEQUENTIAL PROCEDURES FOR MULTIPLE COMPARISON OF TREATMENTS

2002 ◽  
Vol 31 (5) ◽  
pp. 781-793
Author(s):  
Bernard Cerutti ◽  
Toufik Zoubeidi ◽  
David M. Reboussin
2003 ◽  
Vol 2 (4) ◽  
pp. 263-271 ◽  
Author(s):  
Todd A. Schwartz ◽  
Jonathan S. Denne

2018 ◽  
Vol 28 (8) ◽  
pp. 2385-2403 ◽  
Author(s):  
Tobias Mütze ◽  
Ekkehard Glimm ◽  
Heinz Schmidli ◽  
Tim Friede

Robust semiparametric models for recurrent events have received increasing attention in the analysis of clinical trials in a variety of diseases including chronic heart failure. In comparison to parametric recurrent event models, robust semiparametric models are more flexible in that neither the baseline event rate nor the process inducing between-patient heterogeneity needs to be specified in terms of a specific parametric statistical model. However, implementing group sequential designs in the robust semiparametric model is complicated by the fact that the sequence of Wald statistics does not follow asymptotically the canonical joint distribution. In this manuscript, we propose two types of group sequential procedures for a robust semiparametric analysis of recurrent events. The first group sequential procedure is based on the asymptotic covariance of the sequence of Wald statistics and it guarantees asymptotic control of the type I error rate. The second procedure is based on the canonical joint distribution and does not guarantee asymptotic type I error rate control but is easy to implement and corresponds to the well-known standard approach for group sequential designs. Moreover, we describe how to determine the maximum information when planning a clinical trial with a group sequential design and a robust semiparametric analysis of recurrent events. We contrast the operating characteristics of the proposed group sequential procedures in a simulation study motivated by the ongoing phase 3 PARAGON-HF trial (ClinicalTrials.gov identifier: NCT01920711) in more than 4600 patients with chronic heart failure and a preserved ejection fraction. We found that both group sequential procedures have similar operating characteristics and that for some practically relevant scenarios, the group sequential procedure based on the canonical joint distribution has advantages with respect to the control of the type I error rate. The proposed method for calculating the maximum information results in appropriately powered trials for both procedures.


2018 ◽  
Vol 60 (5) ◽  
pp. 893-902
Author(s):  
Huiling Li ◽  
Jianming Wang ◽  
Xiaolong Luo ◽  
Janis Grechko ◽  
Christopher Jennison

2004 ◽  
Vol 08 (04) ◽  
pp. 181-193
Author(s):  
Troy Jones ◽  
Abdulkadir A. Hussein ◽  
Shrawan Kumar

The use of sequential analysis in clinical rehabilitation research allows a spectrum of analyses in the comparison of two or more treatment protocols. Researchers in rehabilitation medicine are increasingly making use of sequential designs in their clinical investigations. This review serves to highlight the optimal use of the classical sequential designs presented by Armitage and Bross in the mid-twentieth century. A discussion of the limitations of this most basic sequential analysis is presented for the information of clinical researchers considering this study design. Examples of the use of classical and group sequential designs addressing both continuous and dichotomous outcomes are provided, and the advantages and disadvantages of classical and group sequential procedures as compared to fixed sample designs are illustrated with rehabilitation examples. As little literature has been published regarding the application of sequential analysis in clinical rehabilitation trials, clinical pharmacological, and medical trials in addition to medical statistical sources were used in this review.


1989 ◽  
Vol 8 (10) ◽  
pp. 1191-1198 ◽  
Author(s):  
K. K. Gordon Lan ◽  
David L. Demets

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