July 25, 2024

Today, the R Analyzer for Large-Scale Assessments (RALSA) package for the R statistical environment has been updated to version 1.4.7. This update replaces the F-statistic with Wald F-statistic in linear regression and fixes a bug in all analysis functions that crashes them when TALIS 3S data is used due to misidentified replicate weights.

Bug fixes

• All analysis functions crashing with TALIS 3S data because of misidentified replicate weights.

New functionality

• The F-statistic in lsa.lin.reg was replaced with Wald F-statistic as a suitable estimator for clustered data. The chi-square statistic is also provided.

Miscellaneous

• Improved documentation.

 

 

April 26, 2024

The R Analyzer for Large-Scale Assessments (RALSA) has been updated to version 1.4.5. This update fixes a number of issues in the graphing capabilities of the descriptive functions and the GUI. In addition to these fixes, the GUI has received various visual improvements and optimizations. The support for ICCS 2022 cycle has been finalized. Here is the full list of changes:

Bug fixes

• When switching between tabs in the GUI, the tab being switched to scrolls down to the position of the previous tab. Now the tabs are scrolled up to their top when the user switches between tabs.
• The GUI part for lsa.convert.data does report an error for unequal length of file names in folder for PISA 2018.
• The GUI part for lsa.convert.data does not show newly released SAV files for PISA 2018.
• The GUI part for lsa.convert.data does not show the files in the inp.folder for PISA 2022.
• Following some changes in package ggplot2, the lsa.pcts.means, lsa.prctls and lsa.bench crash when graphs = TRUE.
• Following the latest changes in R on POSIXCt date formats, lsa.pcts.means, lsa.prctls and lsa.bench were reporting incorrect total times.

Miscellaneous

• Various code changes following the update of R to version 4.4.0.
• Finalized support for the ICCS 2022 cycle.
• Small rearrangement of the graphical elements in the variable dictionaries’ tab in the GUI to make it consistent with the rest of the tabs.
• Improved the welcoming screen animation on loading the GUI.
• Various visual improvements and optimizations in the GUI:
  • Positioning of elements in the workspace;
  • Spacing between elements;
  • Showing and hiding elements depending on user selections;
  • Issuing warning messages;
  • Navigation between fields.
• Improved documentation.

 

 

February 2, 2024

The R Analyzer for Large-Scale Assessments (RALSA) has been updated to version 1.4.0. This update fixes a number of issues, completely revamps the conversion function, updates the conversion of PISA 2015 files, adds support for PISA 2022 and a studies, and countries’ participation in studies and cycles reference table in the GUI help section.

Bug fixes

• lsa.convert.data crashes when converting PISA 2015 data and missing.to.NA = FALSE.
• lsa.convert.data crashes when converting PISA for Development 2019 out of school files.
• lsa.convert.data converts TALIS 3S 2018 ISCED 0.2 as SITES 2006 data.
• lsa.convert.data does not save converted .RData files when converting PISA data prior to its 2015 cycle with missing.to.NA = TRUE.
• lsa.bench crashes when benchmarks are not provided by the user, not using the default benchmarks.
• lsa.crosstabs crashes when one or more of the countries have just one valid value in the bckg.row.var or bckg.col.var (i.e. insufficient data).
• lsa.bin.log.reg crashes when one or more of the countries does not have valid data in the analysis variables.
• Following the last changes of how R handles the POSIX dates and times, lsa.convert.data, lsa.bench, lsa.crosstabs, lsa.corr, lsa.lin.reg and lsa.bin.log.reg report incorrect total times of all operations.
• Following the latest changes in the shiny’s package update to version 1.8.0, when using categorical background variables in the GUI, lsa.lin.reg and lsa.bin.log.reg do not add the contrasts and reference categories in the syntax and do not update user selections.

New functionality

• An interactive reference table with countries’ participation in different studies and cycles was added in the GUI help section which is now split into two parts.

Miscellaneous

• The lsa.convert.data function was rewritten (almost) from scratch replacing the foreign package with haven when importing SPSS files. The conversion is much more efficient now and has a better handling of the user-defined missing values. The previous version is now deprecated and is available as lsa.convert.data2 (to be removed in June of 2025).
• Added support for student test timing files in PISA 2015.
• Added support for the student financial literacy file in PISA 2015.
• Added support for PISA 2022 data.
• Various visual improvements and optimizations in the GUI.
• Improved documentation.

 

 

 

October 26, 2023

The R Analyzer for Large-Scale Assessments (RALSA) has been updated to version 1.3.7. This update focuses mainly on some critical issues that were introduced after the changes in the last versions of R and CRAN policies on package documentation.

Bug fixes

• When a file with school and teacher data merged is imported, the GUI crashes for all analysis functions.

• The GUI does not recognize some populations’ files in different studies when using the lsa.convert.data function and crashes.

Miscellaneous

• Various improvements and optimizations in the GUI workfrlow for all data preparation and analysis functions, including showing and hiding elements depending on the user selections.
• Improved documentation.

 

 

 

June 23, 2023

The R Analyzer for Large-Scale Assessments (RALSA) has been updated to version 1.3.5. This update focuses on adding more functionality to the existing graph capabilities, bug fixes and overall improvement of the workflow, and fixes existing features following updates of packages RALSA depends on. Saving syntaxes from the GUI now appends the new synatx to existing files instead of overwriting them. Support for PIRLS 2021 is now added. Here is the full list of changes:

New functionality

• The descriptive statistics functions (lsa.pcts.means, lsa.prctls, lsa.bench and lsa.crosstabs) now have new arguments that allow definition of custom x- and y-axis labels for the plots. This has also been implemented in the GUI.
• The lsa.crosstabs function now has the possibility to add custom axes’ labels in heat plots. Until now, the function used the row and column variable names to label the axes. The custom axis labels can be added using the graph.row.label and graph.col.label arguments.
• The lsa.pcts.means function now has the possibility to add custom axes’ labels in percentages of respondents within groups and in means’ plots. Until now, the function used the last split and the average variable(s) names to label the axes. The custom axis labels can be added using the arguments perc.x.label, perc.x.label, mean.x.labelsandmean.y.labels.
• The lsa.bench function now has the possibility to add custom axes’ labels in plots of percentages of respondents within performance groups and the mean for continuous variable, if specified. Until now, the function used “Performance Group” and the PVs set name to label the axes for the percentage plots, and “Performance Group” and the mean’s variable name to label the axes of the mean plot. The custom axis labels can be added using the  arguments perc.x.label, perc.x.label, mean.x.label and mean.y.label.
• The lsa.prctls function now has the possibility to add custom axes’ labels in plots of percentages of respondents within groups and percentiles for continuous variables. Until now, the function used the last split variable name to label the axes for the percentage plots, and “Percentiles” and the continuous variables’ names to label the axes of the percentiles plot. The custom axis labels can be added using the  arguments perc.x.label, perc.x.label, prctl.x.label and prctl.y.label.

Miscellaneous

• Added support for PIRLS 2021 data.
• The GUI can now run in RStudio without blocking the console and the session can run and be used on its own. The GUI runs as a background job. In case problems appear with the new way the GUI is started, use ralsaGUIfailsafe() instead of ralsaGUI() function. This will start the GUI using the old methods, but the console will be blocked.
• The graphical functionality in lsa.pcts.means, lsa.prctls, lsa.bench and lsa.crosstabs has been updated after the ggplot2 update to version 3.4.0 where the size aesthetic has been replaced with linewidth in line based geoms.
• lsa.vars.dict now adds the levels’ numeric values before the labels, as suggested by Falk Brese.
• GUI with all functions. Following the updates of the shiny and DT packages the lists of variables lost their formatting (background color and selected rows color). These are now recovered and when rows are selected the variable names and labels are bolded.
• The colors of the radio buttons and check boxes in the GUI have been changed to match the color scheme used in the rest of the application.
• The behavior of the “Save syntax” button for all tabs in the GUI has been changed. When the file with the syntax already exists, the new syntax is appended to the end instead of overwriting the entire file. This is more convenient, as it allows to save all the syntax generated from different tabs in the GUI in a single file.
• The definition of user-defined missing values in the “Recode variables” section in the GUI now uses semicolon as a delimiter.
• Changed the icon for the “Exit” tab and button in the GUI.
• The copyleft character in the footer of the GUI has been changed, now it is displayed properly.
• Various improvements and optimizations in the GUI workfrlow.
• Improved documentation.

Bug fixes

• lsa.convert.data crashes when converting the TIMSS 1995 grade 4 ASA files. Thanks to Maximilian Brinkmann.
• When converting datasets with lsa.convert.data, some of the variable labels contain unrecognized characters. Thanks to Falk Brese.
• When a factor variable has only one level, the “Variable levels” also include NA as a level.
• After updates of the DT package the panels displaying the country and variable names changed to grey and the colors of the selected rows changed.
• In GUI with lsa.convert.data the syntax is not generated and cannot be executed when PISA (both pre-2015 and later) files are used.
• In GUI with lsa.recode.vars the summary table of recodings is printed in the GUI console, but if any NA values are in the “Source_XXXXX” and “New_XXXXX” variable columns, the output is shifted to the left and unreadable for these lines.

If you missed any of the previous updates and want to see other functionality previously added, check the news page on the RALSA support website.

Please share the news!

 

 

 

July 8, 2022

RALSA has been updated to version 1.3.0. This update focuses mainly on bugfixes and improvements in the GUI and its workflow, but also introduces some new features.

New functionality

• The lsa.crosstabs function now has the possibility to produce heatmap graphs (optional). The graphs are included in a separate sheet in the MS Excel output file if save.output = TRUE. If save.output = FALSE, the graphs are added to the list output object in memory and can be printed in R’s graphic device.
• All GUI tabs for data preparation and analysis functions received “Save syntax” and “Copy syntax” buttons, as suggested by Erika Majoros.

Miscellaneous

• Further work on graphics (lsa.crosstabs, lsa.bench, lsa.pcts.means, lsa.prctls):
  • All functions producing graphical representation of the results now have controlled dpi depending on the number of split.vars to better fit the plots and their labels in space;
  • The lsa.prctls function now adds facets when the number of split.vars is greater than two to fix the issue of dot, line and error bar positioning and overlapping on the plot and improve readability.
• Multiple fixes in GUI for better workflow.
• In GUI with lsa.recode.vars the “Old/New variable names” table was merged with the “New variable labels” table. This change was provoked by fixing the bug that the “New variable labels” table was still showing the old variable names, as discovered by Cecilia Björkhammer. Now the workflow is more intuitive.
• Improved documentation.

Bug fixes

• All analysis functions, as well lsa.data.diag, lsa.recode.vars and lsa.vars.dict crash with an error message Error in exists(all.vars(match.call())) : first argument has length > 1 when any of the arguments specifying analysis variables point to objects which contain character vectors containing them. Thanks to Rodolfo Ilizaliturri.
• lsa.prctls – The percentiles on the x-axis are not properly added for every percentile computed. Thanks to Cecilia Bjorkhammer.
• print.lsa.data – The custom print method for lsa.data blocks some common data.table operations.
• lsa.corr – The function crashes when one of the countries has all missing values for one or more variables passed to the bckg.corr.vars. A warning when this occurs was added.
• GUI with lsa.convert.data – When data files only from one country are available in the source folder, the quote at the end of the path passed to inp.folder in the syntax is not closed and the syntax cannot be executed properly. Thanks to Gasper Cankar.
• GUI with lsa.merge.data – When data files only from one country are available in the source folder, the bracket at the end of the list passed to file.types is not closed and the syntax cannot be executed properly. Thanks to multiple teachers during series of workshops delivered in Slovenia.
• GUI with lsa.recode.vars – When new variable names are defined, the table for the new variable labels still displays the old variable names, as shown below. Thanks to Cecilia Bjorkhammer.
• GUI with lsa.data.diag – When the working data set is changed, series of errors are dropped in the R console (missing value where TRUE/FALSE is needed).
• GUI with lsa.pcts.means – When the working data set is changed, an error is dropped in the R console (Error in paste0: object 'Variables' not found) and shown in the interface.
• GUI with lsa.prctls – When the working data set is changed, an error is dropped in the R console (Error in if: argument is of length zero) and shown in the interface.
• GUI with lsa.bench – When a data set is loaded or the working data set is changed, an error is dropped in the R console (Error in paste0: object 'Variables' not found).
• GUI with lsa.crosstabs – When a data set is loaded or the working data set is changed, an error is dropped in the R console (Error in if: argument is of length zero).
• GUI with lsa.corr – When the working data set is changed, an error is dropped in the R console (Error in if: argument is of length zero) and shown in the GUI.
• GUI with lsa.lin.reg – When the working data set is changed, errors are dropped in the R console (Error in if: argument is of length zero and Warning: object 'Variables' not found) and shown in the GUI.
• GUI with lsa.bin.log.reg – When the working data set is changed, errors are dropped in the R console (Error in if: argument is of length zero and Warning: object 'Variables' not found).

 

 

 

May 4, 2022

RALSA has been updated to version 1.2.0. The main accent in this update is introducing graphical representation of the statistics for the percentages and averages, percentiles, and benchmarks. These graphs can be included directly in the exported MS Excel output file or printed in the R’s graphic device. Here is the full list of changes in this build:

New functionality

• The lsa.pcts.means, lsa.bench and lsa.prctls functions now have the possibility to produce graphs (optional). The graphs are included in a separate sheet in the MS Excel output file if save.output = TRUE. If save.output = FALSE, the graphs are added to the list output object in memory and can be printed in R’s graphic device.
• The MS Excel output files from all analysis functions received an additional sheet with warnings (if any) related with the computations. So far these warnings were just printed on screen.

Miscellaneous

• Internal reorganization of the code producing warnings related with the computations and the way they are issued.
• Improved documentation.
• Various code changes following the update of R to version 4.2.0.

Bug fixes

• lsa.pcts.means – when many split variables are added, in some countries some of the rows in the estimates are repeated multiple times by the categories of the split variables.

 

 

 

March 30, 2022

RALSA has been updated to version 1.1.5. The update brings new functionality for an existing analysis type, new data preparation function, improvements and bug fixes. Here is what’s new in this update:

New functionality

• lsa.pcts.means received a new argument, central.tendency, which allows users to compute either the arithmetic mean (default and available so far), median (new) or mode (new) for continuous variables.
• New function, lsa.select.countries.PISA, a utility function that allows the user to select countries of interest from a converted PISA data file (or PISA object residing in memory) and remove the rest of the countries’ data. This is useful when the user does not want to analyze all countries data available in an original a PISA data file.

Miscellaneous

• All analysis functions received a new argument, save.output. If TRUE (default), the output is written into MS Excel file, as it was so far. If FALSE, the output (a list of all different estimates) is printed on screen or can be assigned to an object. The argument is available in command-line use, but not in the GUI.
• Multiple fixes in GUI for better workflow.
• Improved documentation.

Bug fixes

• GUI with lsa.pcts.means does not show the syntax when only splitting variables are chosen for the analysis and the GUI freezes when the analysis is ran.

 

 

 

March 25, 2022

Save the dates!

The International Educational Research and Evaluation Institute (https://www.ineri.org) is organizing a three-day online training on using the R Analyzer for Large-Scale Assessments (RALSA) R package to analyze large-scale assessments’ and surveys’ data. The three-day training will take place from April 25 till April 27, 2022. The training includes both lectures and hands-on practice sessions.

The agenda for the training can be found here.

Please note that the number of seats for the training is limited to 15. Follow the link below to register for the training (no login is required to submit your answers).

The fee for the training is EUR 225, non-refundable (fees for no-show attendants can be used in future trainings). The registration will be confirmed once the payment has been received.

Please feel free to share this with your contacts.

If you have any further questions related to the training, do not hesitate to write us at ralsa@ineri.org

 

 

 

February 4, 2022

RALSA was updated to version 1.1.0. The update brings one more analysis type, a new feature for two of the existing analysis types, support for a new study, support for an additional datasets type within a supported study, many bugfixes, and a lot of improvements. Here is what’s new:

New functionality

• New analysis function, lsa.crosstabs. It computes a two-way table (crosstabulations) and Rao-Scott first- and second-order design corrected chi-square statistics. The Rao-Scott adjustment is needed because of the clustered design of the large-scale assessments and surveys data.
• Added the possibility to include two-way interaction terms in lsa.lin.reg and lsa.bin.log.reg. The interactions can be between two categorical variables, categorical and continuous, continuous and continuous, categorical with PVs, continuous with PVs, and PVs with PVs.
• Added a new printing method for lsa.data objects in memory. It prints the study name, cycle, respondent type(s), total number of countries, key, if the data has user-defined missing values or not, and a snippet of the data.

Support for a new study added

• Support for the IEA Responses to Educational Disruption Survey (REDS) 2021 was added.

Bug fixes

• All analysis functions. When “IDCNTRY” is added explicitly to the list of split.vars and include.missing = TRUE, the function crashes with the following error message. Thanks to Laura Ringiene.
• lsa.prctls function. When computations involve PVs, the estimates of specific percentile appear in a wrong column, e.g. the 25^th percentile columns contain the estimates for the 5^th percentile columns and the other way around. Thanks to Laura Ringiene.
• lsa.data.diag function. When the tables are exported to Excel, the “Index” sheet appears as the first one, but the file opens with the sheet with statistics for the first variable on the front.
• GUI with lsa.data.diag and all analysis functions. When using the GUI and an output file with the same name as the specified is already opened, the GUI crashes when the respective function tries to write the new output file.
• lsa.bin.log.reg function. The coefficients output is not sorted properly by the names of the independent variables and the desired order.
• GUI with lsa.corr function. When the loaded data file in “Correlations” analysis contains no PVs, the radio buttons for choosing between Pearson and Spearman correlation are not shown.
• GUI with all functions. If any error occurs during a function execution (i.e. after pressing the Execute syntax button), the GUI crashes.

Miscellaneous

• Added support for the recently released IEA eTIMSS 2019 Problem Solving and Inquiry (PSI) tasks’ data.
• The RALSA logos in the GUI and GUI start-up screen was replaced with higher-resolution images.
• Various visual improvements of the GUI.
• Updated and improved documentation.

 

 

 

November 16, 2021

RALSA was presented at the International Research Conference (IRC) organized by the International Association for the Evaluation of Educational Achievement (IEA). The conference is held in Dubai in three modes — onsite, online, and hybrid.

The presentation given at this conference introduced the package, its internal structure and workflow, as well as the plans for further developments. It also provided comparisons between RALSA and other software packages for analyzing large-scale assessment data. We would like to thank the IEA for giving us this opportunity, as well as to all session participants for their questions and comments. The full presentation is available here here.

 

 

 

October 21, 2021

RALSA was updated to version 1.0.2. This is a maintenance update and includes some bugfixes, dropping a package dependency, and some improvements. Here is what’s new:

Bug fixes

• lsa.pcts.means function crashes with an error message when no split variables are added and both background variables and PVs are added to compute means for. Thanks to an anonymous RALSA user.
• lsa.bin.log.reg function crashes when the variable name passed to bin.dep.var contains numeric characters.
• lsa.lin.reg function crashes when the variable name passed to bckg.dep.var contains numeric characters.
• When used in the GUI, the lsa.recode.vars assigns the new value labels to the recoded values in incorrect order. Thanks to multiple workshop participants at the ECER 2021 pre-conference training.

Miscellaneous

• The gdata package is no longer needed by RALSA.
• Start up and warning messages when dependencies are loaded during GUI start are not displayed anymore.

To obtain the new version, just update all of your R packages executing the following command:

update.packages(ask = FALSE)

Enjoy!

For questions, training requests, feature requests, and bug reports, please write to ralsa@ineri.org

 

 

 

October 4, 2021

We are very happy to announce a new publication on the RALSA package in the Springer Open Large-scale Assessments in Education journal (an IEA-ETS Research Institute Journal). The publication entitled “RALSA: the R analyzer for large-scale assessments” is a general presentation of the R Analyzer for Large-Scale Assessments (RALSA), an R package for analyzing data from studies using complex sampling and assessment designs. The paper presents the architecture of the package, the overall workflow and illustrates some basic analyses using it. The package is open-source and free of charge. RALSA is the first comprehensive R package, designed for the user experience and has some distinctive features. For more details and access the full open access publication, refer here.

 

 

 

September 2, 2021

The first workshop on using RALSA was delivered as part of the annual European Conference on Educational Research (ECER) 2021 conference. This one-day workshop was delivered within the ECER 2021 pre-conference. We would like to thank all attendants for their active participation in this one-day event. We would also like to express our special gratitude to the the European Educational Research Association (EERA) and the EERA Network 9 for giving us the opportunity and for their help in organizing and delivering this training. We hope that this workshop will become a regular part of future ECER meetings.

 

 

 

June 12, 2021

A publication on the RALSA package software design and implementation was published in the MDPI’s Psych journal – “RALSA: Design and Implementation” (https://doi.org/10.3390/psych3020018) – as part of the journal’s special issue Computational Aspects, Statistical Algorithms and Software in Psychometrics. The paper presents the technical aspects of RALSA – the overall design and structure of the package, its internal organization, and the structure of the analysis and data preparation functions. The use of the data.table package for memory efficiency, speed, and embedded computations is explained through examples. The central aspect of the paper is the utilization of code reuse practices to the achieve consistency, efficiency, and safety of the computations performed by the analysis functions of the package. The comprehensive output system to produce multi-sheet MS Excel workbooks is presented and its workflow explained. The paper also explains how the graphical user interface is constructed and how it is linked to the data preparation and analysis functions available in the package. This is an open access publication and can be accessed here.

 

 

 

May 28, 2021

RALSA was updated to version 1.0.1. 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

• All analysis functions. Some functions in base R were updated and their behavior has changed causing crashes in the analysis functions with first argument has length \> 1 error messages.

• lsa.vars.dict function. When there are just two levels for a factor variable, the second level in ?Variable levels? ends without a single quote.

• Occasionally, the lsa.data.diag freezes R with a question mark in the console and eventually crashes the R session when split.vars are provided.

Miscellaneous

• Various optimizations in the lsa.corr, lsa.lin.reg and lsa.bin.log.reg functions.

• The lsa.data.diag function now has user interruption handling with a message.

 

 

 

April 28, 2021

We are happy to announce that RALSA (the R Analyzer for Large-Scale Assessments) has received an update. The package version was incremented to 1.0.0 because it  has reached maturity and stability. It brings a new function, many improvements and bug fixes. Here is what’s new:

 

 

 

March 15, 2021

We are happy to announce that RALSA (the R Analyzer for Large-Scale Assessments) has received an update (v0.90.3). It brings bug fixes and improvements. Here is what’s new:

Bug fixes

• lsa.convert.data function. The function crashes when the different cycles of the study change the case of the file names and their extensions. Thank to Yuan-Ling (Linda) Liaw.
• lsa.recode.vars function. If the recoding instruction ends with semicolon, the function crashes.
• lsa.bin.log.reg function. The function crashes if some specific patterns are found in the binary dependent variable names.
• lsa.pcts.means function. Some missing estimates in columns Mean, Mean_SE, Mean_SVR, Mean_MVR, SD_SE and SD_MVR when the groups are too small.
• All analysis functions crash using SITES 2006 data when only mathematics teacher or only science teacher data are used.
• lsa.pcts.means function. Some estimates using CivED data were incorrect.
• lsa.pcts.means function. Missing estimates in some columns for specific combination of splitting variables.

Miscellaneous

• The ISO argument in lsa.convert.data is now case-insensitive.
• file.types and ISO arguments in lsa.merge.data are now case insensitive.
• The error messages in lsa.recode.vars are improved.

For questions, feature requests, training requests, and bug reports, please write to ralsa@ineri.org.

 

 

 

January 2, 2021

We are happy to announce that RALSA (the R Analyzer for Large-Scale Assessments) has received an update (v0.90.2). Here is what’s new:

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.

Bug fixes

• lsa.convert.data function. Unrecognized characters in factor levels are now fixed. Such were, for example the levels of the number of books variable in PIRLS 2016 and other cycles which displayed unrecognized characters instead of instead of “-”.
• lsa.convert.data function. For some variables categories have the same labels as the missing ones in other variables and are improperly converted as missing.
• GUI. When categorical variables are added in the list of Independent background categorical variables in linear and logistic regression, the number of categories (N cat. column) and the drop-down menu for the reference categories (Ref. cat. column) include the missing values as well.
• When loading or switching to a tab in the GUI, it is scrolled to the position where the previous tab was scrolled to.

Miscellaneous

• Various improvements for the GUI elements location.
• Improved documentation.
• Links to the documentation for each functionality RALSA supports were added to the Help section of the GUI.
• Improved messages, warnings and error messages.

The binary packages for the new version will be available tomorrow (January 4, 2021), the impatient ones can install from source now. To update to the new version, just update your R packages:

update.packages(ask = FALSE)

Those who do not have RALSA installed yet, follow the installation instructions.

For questions, feature requests, training requests, and bug reports, please write to ralsa@ineri.org.

 

 

 

November 10, 2020

RALSA v.0.90.1 was released!

We are proud to announce the first release of RALSA. After all the hard work of development, the first version of the R Analyzer for Large-Scale Assessments (RALSA) came to life. RALSA targets both the experienced R users, as well as those who do not have technical skills. Thus, along with the traditional command-line R interface, a Graphical User Interface is made available.

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

The R Analyzer for Large-Scale Assessments (RALSA) is an R package 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). The number for both of these will increase in future.

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

In addition to the traditional command-line R interface, RALSA introduces a Graphical User Interface for the users who lack the technical skills.

Currently, RALSA supports the following functionality: