Abstract Details
Activity Number:
|
562
|
Type:
|
Contributed
|
Date/Time:
|
Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Biometrics Section
|
Abstract #312606
|
View Presentation
|
Title:
|
Models for Correlated Mixed Discrete and Continuous Random Variables in Clinical Trials
|
Author(s):
|
Sergei Leonov*+ and Bahjat Qaqish
|
Companies:
|
AstraZeneca and University of North Carolina at Chapel Hill
|
Keywords:
|
marginal distribution ;
multivariate distribution ;
extreme correlation ;
multiple endpoints ;
copula
|
Abstract:
|
Modeling and simulation of correlated random variables is important for evaluating operating characteristics of various designs that involve multiple endpoints, some of which may be discrete (e.g., number of events) and some continuous (e.g., change of a continuous score). There exist efficient algorithms to address the problem of generating multivariate distributions with given marginals and given correlation structure, in particular NORTA (NORmal To Anything, Cario and Nelson (1997)). For numerical implementation of such algorithms, it is important to know the extreme values of pairwise correlations, which may be less than 1 in absolute value. We provide closed-form expressions for several classes of multivariate distributions that involve both discrete and continuous endpoints and illustrate the performance of algorithms via several examples.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.