New version of Stat-JR missing data template released.
2 May 2017
New version of 'one pass' missing data Stat-JR template (2LevelMissingOnePass) released.
A new version of the Stat-JR template, 2LevelMissingOnePass, has just been released (28th April 2017); this template allows users to handle missing data in datasets with multilevel structures using a fully Bayesian procedure (see Goldstein et al (2014) for further details).
The new version of the template (v1.0.1) contains bug fixes for higher-level responses. There are also minor improvements to starting values functionality, and DIC and deviance have now been disabled.
To obtain the new version, download the zip file Imputation for Multilevel Models with Missing Data Using Stat-JR from the Missing Data webpage. As well as a new version of the template, the zip file contains minor changes to the tutmiss.dta example dataset, and a new 2-level example dataset, tutmiss_lev2.dta.
The supporting manual, Missing Data with Stat-JR, also available from the Missing Data webpage, has been updated in light of these changes as well.