December 2015
Intermediate to advanced
364 pages
19h 31m
English
book
Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods
by Sandeep Menon, Richard C. Zink
Content preview from Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods
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4.7 SAS MACRO BSMED
4.7.1 Implementation of BSMED
4.7.1.1 Detailed Macro Options
In this section, we
present the details of SAS macro,
BSMED,
for Bayesian survival meta-experimental design. As discussed in 4.2 Meta Design Setting, the macro BSMED requires two
input data sets, namely, the current data and the historical data
(optional), 11 input variables, and one output file (optional). Names and Descriptions of Input Variables and Design Values shows the names and descriptions of the input variables
and the design values in the SAS macro.
|
Data
|
Names in macro
|
Description
|
|---|---|---|
|
Historical
|
a0
|
Discounting parameter
|
sigma0
|
Initial variance of
|
|
sigma1 ... |
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