Stat-JR Features

Stat-JR is a general purpose statistical package with wide-ranging and flexible functionality. Its features include:


Ability to communicate with other statistical software

A choice of interfaces


In-house MCMC engine

Schematic overview

The figure below gives an overview of how the system works:


Screenshots of the TREE interface

Choosing a template

Stat-JR uses a modular system of templates, each defining a certain function: some fit models, others plot charts, some produce data summaries, and so on:

TREE screenshot 1

Specifying inputs

Once the user has chosen a template (and dataset), inputs specific to those choices are then entered:

TREE screenshot 2

Interim outputs

Having specified all the inputs the template requests, Stat-JR produces the files it needs to complete the desired execution, together with useful descriptive resources such as equations (LaTeX):

TREE screenshot 3

Template execution finished

Once the desired execution has run, the final output files are returned; here we see some model results (other outputs would be accessible via the drop-down list just above the output pane):

TREE screenshot 4

Screenshots of the DEEP interface

Conditional text

The content of the eBook can be dictated by choices the user has made as he/she is reading through; here the user has chosen the fixed effects for a model which, for comparison, is fitted both with, and without, random effects for school (at level 2):

DEEP screenshot 1

Here the variance partition coefficient is returned based on the user's model choices; these will be calculated anew every time the user changes the model specification:

DEEP screenshot 2

Interoperability with other statistical software

Both TREE and DEEP can interoperate with other statistical software. Here is an example in which a plot reflecting the user's specification has been produced using R, with both the plot, and the R script used to derive it, returned as content in the eBook:

DEEP screenshot 3