In a clinical trial with repeated measures designs, outcomes are often taken from subjects at fixed timepoints. The focus of the trial may be to compare the mean outcome in two or more groups at some prespecified time after enrollment. In the presence of missing data auxiliary assumptions are necessary to perform such comparisons. One commonly employed assumption is the missing at random assumption (MAR). The 'samon' package allows the user to perform a (parameterized) sensitivity analysis of this assumption. In particular it can be used to examine the sensitivity of tests in the difference in outcomes to violations of the MAR assumption. The sensitivity analysis can be performed under two scenarios, a) where the data exhibit a monotone missing data pattern (see the samon() function), and, b) where in addition to a monotone missing data pattern the data exhibit intermittent missing values (see the samonIM() function).
Package details 


Author  Daniel O. Scharfstein [aut], Aidan McDermott [aut, cre] 
Date of publication  20170815 22:02:24 UTC 
Maintainer  Aidan McDermott <[email protected]> 
License  GPL2 
Version  4.0.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.