Search found 40 matches

by CMM
Mon Feb 11, 2019 3:09 pm
Forum: MLwiN user forum
Topic: MLwiN 3.03 released
Replies: 0
Views: 90

MLwiN 3.03 released

MLwiN 3.03 has now been released. For details of bug fixes go to: https://bristol.ac.uk/cmm/software/mlwi ... fixes.html

Upgrade to latest version: https://www.cmm.bristol.ac.uk/clients/softwaredownload/
by CMM
Mon Dec 17, 2018 3:50 pm
Forum: Stat-JR user forum
Topic: Stat-JR 1.0.6 released
Replies: 0
Views: 410

Stat-JR 1.0.6 released

We are pleased to announce the release of version 1.0.6 of Stat-JR. This version has all the existing functionality of Stat-JR including its own MCMC estimation engine, interoperability with many software packages, three different interfaces (web, eBook and workflow) and its statistical analysis ass...
by CMM
Thu Mar 01, 2018 2:20 pm
Forum: MLwiN user forum
Topic: MLwiN 3.02 released
Replies: 0
Views: 4004

MLwiN 3.02 released

MLwiN 3.02 has now been released. For details of bug fixes go to: http://bristol.ac.uk/cmm/software/mlwin/bugs/fixes.html

Upgrade to latest version: https://www.cmm.bristol.ac.uk/clients/softwaredownload/
by CMM
Tue Nov 21, 2017 5:10 pm
Forum: Stat-JR user forum
Topic: Stat-JR 1.0.5 released
Replies: 0
Views: 3553

Stat-JR 1.0.5 released

We are pleased to announce the release of version 1.0.5 of Stat-JR. This release contains many bug fixes and new features: http://www.bristol.ac.uk/cmm/software/statjr/bugs/fixes.html http://www.bristol.ac.uk/cmm/software/statjr/features/new105/ A major new functionality is the introduction of the S...
by CMM
Fri Sep 01, 2017 11:41 am
Forum: R2MLwiN user forum
Topic: R2MLwiN 0.8-5 released
Replies: 0
Views: 1996

R2MLwiN 0.8-5 released

R2MLwiN 0.8-5 has now been released. For details of new features and bug fixes go to: http://cran.r-project.org/web/packages/R2MLwiN/NEWS or for further details regarding bugs visit: http://www.bristol.ac.uk/cmm/software/r2mlwin/r2mlwin-knownbugs.html For information on installation/upgrading see: h...
by CMM
Tue Jul 11, 2017 10:39 am
Forum: R2MLwiN user forum
Topic: R2MLwiN 0.8-4 released
Replies: 0
Views: 2008

R2MLwiN 0.8-4 released

R2MLwiN 0.8-4 has now been released. For details of new features and bug fixes go to:
http://cran.r-project.org/web/packages/R2MLwiN/NEWS

For information on installation/upgrading see:
http://www.bris.ac.uk/cmm/software/r2mlwin/
by CMM
Wed May 31, 2017 3:47 pm
Forum: MLwiN user forum
Topic: MLwiN 3.01 released
Replies: 0
Views: 2098

MLwiN 3.01 released

MLwiN 3.01 has now been released. For details of bug fixes go to: https://www.bristol.ac.uk/cmm/software/ ... fixes.html

Upgrade to latest version: https://www.cmm.bris.ac.uk/clients/softwaredownload/
by CMM
Fri Mar 03, 2017 11:16 pm
Forum: MLwiN user forum
Topic: MLwiN 3.00 released
Replies: 0
Views: 2214

MLwiN 3.00 released

MLwiN 3.00 has now been released. For details of bug fixes go to: http://www.bristol.ac.uk/cmm/software/mlwin/bugs/fixes.html For detail on changes and new features see: http://www.bristol.ac.uk/cmm/software/mlwin/features/mlwin-3-00.html Upgrade to latest version: http://www.cmm.bristol.ac.uk/clien...
by CMM
Thu Nov 24, 2016 4:05 pm
Forum: Realcom user forum
Topic: Missing data: new Stat-JR functionality to support analyses of incomplete datasets
Replies: 0
Views: 2026

Missing data: new Stat-JR functionality to support analyses of incomplete datasets

There are now three principal Stat-JR templates available to support handling missing data in multilevel generalised linear models. These are typically much quicker than the equivalent executions in REALCOM-IMPUTE, and allow for greater flexibility too. Please note, though, that these templates have...
by CMM
Thu Nov 24, 2016 4:03 pm
Forum: Stat-JR user forum
Topic: Missing data: new Stat-JR functionality to support analyses of incomplete datasets
Replies: 0
Views: 1815

Missing data: new Stat-JR functionality to support analyses of incomplete datasets

There are now three principal Stat-JR templates available to support handling missing data in multilevel generalised linear models; these use two different approaches. The first two templates use ‘multiple imputation’ which is a widely used procedure that will handle a large number of models: a 2-le...