Stat-JR: a software environment for promoting interactive complex statistical modelling. 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.
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Goldstein, Harvey; Browne, William J.; Charlton, Christopher: A Bayesian model for measurement and misclassification errors alongside missing data, with an application to higher education participation in Australia (2018)
- Zhengzheng Zhang and Richard Parker and Christopher Charlton and George Leckie and William Browne: R2MLwiN: A Package to Run MLwiN from within R (2016) not zbMATH
- George Leckie: runmixregls: A Program to Run the MIXREGLS Mixed-Effects Location Scale Software from within Stata (2014) not zbMATH