RALSA v1.3.0 (2022-07-08)

This update focuses mainly on bugfixes and improvements in the GUI and its workflow, but also introduces some new features.

Bug fixes

New functionality

Miscellaneous

RALSA v1.2.0 (2022-05-04)

Bug fixes

New functionality

Miscellaneous

RALSA v1.1.5 (2022-03-30)

Bug fixes

New functionality

Miscellaneous

RALSA v1.1.0 (2022-02-04)

Bug fixes

New functionality

New study added

Miscellaneous

RALSA v1.0.2 (2021-10-21)

This is a maintenance version fixing some bugs and removing package dependency.

Bug fixes

Miscellaneous

RALSA v1.0.1 (2021-05-28)

This is a maintenance version following the update of base R to v4.1.0 where some functions’ behavior has changed and cause crashes in the analysis functions.

Bug fixes

Miscellaneous

RALSA v1.0.0 (2021-04-28)

Bug fixes

New functionality

Miscellaneous

RALSA v0.90.3 (2021-03-15)

Bug fixes

Miscellaneous

RALSA v0.90.2 (2021-01-02)

Bug fixes

New study cycles added

TIMSS 2019 is now fully supported.

New study added

PISA for Development is now supported, as requested by David Joseph Rutkowski.

Miscellaneous

RALSA v0.90.1 (2020-10-26)

The first version of the R Analyzer for Large-Scale Assessments (RALSA) is released. RALSA targets both the experienced R users, as well as those less technical skills. Thus, along with the traditional command-line R interface, a Graphical User Interface is featured.

Note that this is a “first release” version, so some bugs are expected.

RALSA is is used for preparation and analysis of data from large-scale assessments and surveys which use complex sampling and assessment design. Currently, RALSA supports a number of studies with different design and a number of analysis types (see below). Both of these will increase in future.

RALSA is a free and open source software licensed under GPL v2.0.

Currently, RALSA supports the following functionality:

All data preparation and analysis functions automatically recognize the study design and apply the appropriate techniques to handle the complex sampling assessment design issues, while giving freedom to tweak the analysis (e.g. change the default weight, apply the “shortcut” method in TIMSS and PIRLS, and so on).

Currently, RALSA can work with data from all cycles of the following studies (more will be added in future):