News...

• 24 Sep 2019: Stat-JR 1.0.7 has now been released! View the bug fixes.
• 10 Dec 2018: Stat-JR 1.0.6 has now been released! View the bug fixes.
• 21 Nov 2017: Stat-JR 1.0.5 has now been released! View the bug fixes and new features.
• 28 Apr 2017: Missing data: new version of 'one pass' Stat-JR template (2LevelMissingOnePass) released.
• 23 Nov 2016: Missing data: new Stat-JR functionality to support analyses of incomplete datasets.
• 27 Jun 2016: Stat-JR 1.0.4 has now been released! View the bug fixes.
• 18 May 2016: One-day Stat-JR Workflow & eBook Workshop, to take place on 4th July 2016 in Bristol; closing date for applications 17th June 2016.
• 05 Nov 2015: Stat-JR 1.0.3 has now been released! View the bug fixes.
• 13 Mar 2015: updated version of Multiple imputation for multilevel models with missing data template, eBook and accompanying pdf released.
• 19 Dec 2014: updated version of Multiple imputation for multilevel models with missing data template and eBook released.
• 29 Sep 2014: Stat-JR 1.0.2 has now been released! View the bug fixes.
• 09 Apr 2014: Multiple imputation for multilevel models with missing data - there is now a template, and supporting eBook, available for download which conduct multiple imputation for 2-level models in Stat-JR. This incorporates the existing Realcom procedures, but provides a very much faster implementation.
• 25 Mar 2014: Stat-JR 1.0.1 has now been released! View the bug fixes.
• 18 Dec 2013: Stat-JR 1.0.0 released.
• 16 Jan 2013: Stat-JR 0.2 (second beta version) released. View new features.
• 17 May 2012: Stat-JR 0.1 (beta version) released

Overview

The ideas behind Stat-JR (pronounced "stature") were the brainchild of Jon Rasbash and have been developed since September 2009 by Bill Browne and colleagues at both the Centre for Multilevel Modelling, in the University of Bristol, and Electronics and Computer Science, at the University of Southampton, as part of the ESRC nodes e-Stat, Lemma II and LEMMA 3, and more recently as part of the ESRC research grant The use of interactive electronic-books in the teaching and application of modern quantitative methods in the social sciences.

• Stat-JR is a universal gateway to many specialised statistical packages, providing tools to help users learn about statistical methods and their implementation in a range of statistical packages.
• As well as offering such inter-operability, Stat-JR has its own estimation engines which can fit models no other statistical software caters for.
• Stat-JR offers a choice of different interfaces, including a point-and-click menu-driven interface (TREE), a command line interface, and an eBook-reader (DEEP); the latter allows users to produce interactive reports guiding readers through analyses.
• The modular structure of templates allows users to extend Stat-JR's functionality, facilitating the development, and dissemination, of new statistical methodologies and model families.
• See the manuals, FAQs and user forum for further details of these, and many other, features.

Stat-JR has been developed using the Python programming language with the view that statistical users of all abilities can contribute to the development of new templates to answer specific questions.

We would like to take the opportunity to acknowledge Python, MathJaX and the various Python and JavaScript packages that comes as part of the Stat-JR download. We would like to acknowledge the hard work done by the developers of all these free software packages.

Ordering Stat-JR

Stat-JR is distributed with MLwiN, and is therefore free to UK academics, and otherwise available for purchase.

Further details can be found on our Ordering & Installing Stat-JR page.

Making contact

If you have any queries regarding Stat-JR, you can check the FAQs, use the forum, or report any bugs you find via the bug report form.