The Centre for Multilevel Modelling, University of Bristol, has the following news items:
1. Stat-JR & eBook (one-day) Workshop, places available on 4 July
2. R2MLwiN: new version released, and pre-print article available
Full details below:
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1) Stat-JR Workflow & eBook Workshop, 4th July, University of Bristol
This is a one-day workshop taking place only on Monday 4th July 2016 (not additionally on 8th July as previously advertised).
Stat-JR is a statistical environment that allows you to explore, analyse and display data. Whilst Stat-JR has its own in-house statistical functionality which uses Python and also C++, it can additionally interoperate with a wide variety of other statistical software packages, such as R and MLwiN (
http://www.bristol.ac.uk/cmm/software/statjr/).
Users have a choice of Stat-JR interfaces: a chiefly menu-driven interface (TREE), an eBook-reader (DEEP), and (in the upcoming release in Spring 2016) a new workflow interface. The workflow interface uses the Blockly visual programming system, extending the selection of blocks available to include those that perform common statistical processes. As such, it has a user-friendly front-end which allows users to build up a workflow using different blocks, with each block conceptually representing a particular section of code.
Stat-JR is distributed with MLwiN, and is therefore free to UK academics and otherwise available for purchase (see our Ordering & Installing Stat-JR page for more information).
Instructors:
Dr Richard Parker, Professor Bill Browne, Mr Chris Charlton
For further information about the workshop and to make an application, please go to:
Please note the closing date for applications is Friday 17th June 2016.
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2) R2MLwiN: new version released, and pre-print article available
R2MLwiN is an R command interface to the MLwiN multilevel modelling software package, allowing users to fit multilevel models using MLwiN from within the R environment. The latest version of R2MLwiN (0.8-2) was released on CRAN on 12th April 2016, and there is also a preprint of a journal article describing R2MLwiN (in press with the Journal of Statistical Software) available here:
http://www.bris.ac.uk/cmm/media/r2mlwin/article/Zhang_et_al.pdf