TY - JOUR
T1 - Statistical inference for clinical trials with binary responses when there is a shift in patient population
AU - Yang, Lan Yan
AU - Chi, Yunchan
AU - Chow, Shein Chung
PY - 2011/5/1
Y1 - 2011/5/1
N2 - In clinical research, it is not uncommon to modify a trial procedure and/or statistical methods of ongoing clinical trials through protocol amendments. A major modification to the study protocol could result in a shift in target patient population. In addition, frequent and significant modifications could lead to a totally different study that is unable to address the medical questions that the original study intended to answer. In this article, we propose a logistic regression model for statistical inference based on a binary study endpoint for trials with protocol amendments. Under the proposed method, sample size adjustment is also derived.
AB - In clinical research, it is not uncommon to modify a trial procedure and/or statistical methods of ongoing clinical trials through protocol amendments. A major modification to the study protocol could result in a shift in target patient population. In addition, frequent and significant modifications could lead to a totally different study that is unable to address the medical questions that the original study intended to answer. In this article, we propose a logistic regression model for statistical inference based on a binary study endpoint for trials with protocol amendments. Under the proposed method, sample size adjustment is also derived.
UR - http://www.scopus.com/inward/record.url?scp=79953194135&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79953194135&partnerID=8YFLogxK
U2 - 10.1080/10543406.2010.481803
DO - 10.1080/10543406.2010.481803
M3 - Article
C2 - 21442518
AN - SCOPUS:79953194135
SN - 1054-3406
VL - 21
SP - 437
EP - 452
JO - Journal of Biopharmaceutical Statistics
JF - Journal of Biopharmaceutical Statistics
IS - 3
ER -