Major Update: lissyrtools R Package Version 0.2.0 Released
We are pleased to announce the release of version 0.2.0 of the lissyrtools R package. This version introduces several improvements aimed at making the use of LIS and LWS microdata more efficient, clear and better structured for researchers—whether working locally or via the LISSY remote execution system.
One of the most significant updates is the ability to develop and test your full code workflow locally using built-in sample datasets. This facilitates debugging and testing by taking full advantage of user-friendly IDE features, without needing to submit jobs to LISSY during the exploratory phase. This feature is intended to streamline the process from development to execution.
Version 0.2.0 also introduces the new lissyuse() function, which allows users to load harmonized datasets from over 50 countries with a single line of code. It automatically merges household-level and person-level data based on selected variables, offering a straightforward entry point to the dataset.
The package includes a broader set of functions for computing weighted aggregates—such as means, counts, percentiles, poverty rates, and inequality indices. Many of these functions now include support for subgroup disaggregation via a by argument. All major functions handle sampling weights internally, which can help reduce errors and simplify analysis for users less familiar with survey weighting procedures in R.
Weighted percentile calculations have been standardized across functions. Users can choose between two consistent methods, with documentation available to guide usage and selection. This ensures that poverty thresholds, inequality indicators, and other key statistics follow a coherent logic throughout the package.
The layout of the displayed results has also been improved: printed outputs are now grouped by country and sorted by year, with clear formatting that supports comparison across time and countries. For those wishing to visualize results, the new structure_to_plot() function converts results into tidy data frames that integrate seamlessly with ggplot2.
For users working with multiple datasets or reviewing metadata, this release introduces a set of single-line functions executable directly in the local environment. These functions provide quick access to country coverage, available years, survey names, and detailed variable-level metadata—including labels, country-specific categories, notes, and variable availability over time. The tools are intended to support analysis planning, variable auditing, and cross-dataset comparability, serving as a complement to METIS and Compare.It.
The aim of this release is to address common challenges in working with LIS and LWS data—whether in data access, preparation, analysis, or visualization. It is intended to facilitate efficient and organized analysis, whether focused on a single country or cross-national comparisons.
For full documentation, example code, and installation details, please visit the lissyrtools website. The site now includes a searchable reference section and a changelog to track updates. If you encounter issues or bugs, we welcome your feedback and encourage you to get in touch from here.