
Changelog
lissyrtools 0.2.1 (2025-09-15)
New functions
-
run_weighted_absolute_poverty(): Measures absolute poverty based on a fixed monetary threshold. -
check_github_version(): Retrieves the current version oflissyrtoolsin GitHub.
Major changes
- Added logical argument
averagetorun_weighted_percentiles(). When set toTRUEit computes the weighted mean of a variable within each defined percentile group.
Minor changes
- The
byargument inrun_weighted_count(),run_weighted_mean()andrun_weighted_percentiles()is now less restrictive. It accepts additional named variables beyond those defined inlis_categorical_variables,lws_wealth_categorical_variables, orinum. - Applied corrections in
structure_to_plot(), standardizeddnamecolumn values across structures, and renamed a column todistribution_groupin the third structure. - Deleted columns
lisppp,cpi, andpppafter each use ofapply_ppp_adjustment(). This allows the function to be used immediately afterwards, with another variable. - Added the argument
daily_poverty_lineon the following functions:run_weighted_poverty_shortfall()andrun_weighted_poverty_shortfall().
lissyrtools 0.2.0 (2025-06-04)
New functions
🔧 Adjustment & Equivalisation
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apply_iqr_top_bottom_coding(): Applies interquartile range-based top and bottom coding. -
apply_oecd_equivalisation(): Applies the OECD equivalence scale. -
apply_sqrt_equivalisation(): Applies square-root equivalisation. -
apply_ppp_adjustment(): Adjust monetary variables for inflation and PPP
📊 Weighted Statistics
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run_weighted_count(): Computes weighted counts in absolute and percentage terms. -
run_weighted_mean(): Computes weighted means. -
run_weighted_percentiles(): Computes weighted percentiles or shares using type 2 or type 4 definitions. -
run_weighted_ratios(): Computes percentile ratios (e.g. P90/P10). -
run_weighted_gini(): Calculates the Gini coefficient. -
run_weighted_atkinson(): Computes the Atkinson inequality index. -
run_weighted_relative_poverty(): Measures relative poverty based on a median threshold. -
run_weighted_poverty_shortfall(): Computes absolute and relative poverty shortfalls (poverty gap). -
run_weighted_poverty_gap_index(): Calculates the poverty gap index.
📈 Plotting
-
structure_to_plot(): Transforms output into tidy data for plotting withggplot2.
🌍 Country, Year, and Survey Access
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get_countries_lis(): Prints available countries in LIS. -
get_countries_lws(): Prints available countries in LWS. -
get_years_lis(): Prints available years for each country in LIS. -
get_years_lws(): Prints available years for each country in LWS. -
get_surveys_lis(): Prints surveys used for each country in LIS. -
get_surveys_lws(): Prints surveys used for each country in LWS.
🔍 Variable Information
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variable_labels(): Retrieves variable labels. -
variable_country_specific_categories(): Gets country-specific categories for such variables. -
variable_exists(): Checks the years that a variable exists for a given country series. -
variable_has_note(): Checks whether a variable has an associated note.
Major changes
- Expanded Local Sample Data: Increased the number of sample datasets available for local use, supporting more flexible and practical development and testing workflows.
- New Variable and Data Availability Utilities: Introduced a set of functions for local use, to retrieve country/year/survey availability and variable-level metadata, centralizing access to crucial documentation and reducing cognitive fatigue by minimizing tab/window switching.
-
Unified Percentile Computation: A new function,
run_weighted_percentiles(), now centralizes the computation of weighted percentiles, supporting both Type 2 and Type 4 estimation methods as described in Hyndman & Fan (1996). This ensures consistency across all functions that depend on percentile-based logic, such asrun_weighted_ratios(),apply_iqr_top_bottom_coding(), and the one that compute relative poverty figures:run_weighted_relative_poverty(),run_weighted_poverty_shortfall()andrun_weighted_poverty_gap_index(). -
Group-Level Analysis via
byArgument:run_weighted_percentiles(),run_weighted_mean()andrun_weighted_count()now accept abyargument, allowing the disaggregation of results by categorical variables (e.g. region, gender) includinginumvariables in LWS datasets. -
Improved Output and Visualization Readiness:
Cleaner Output Structure: Results are now printed in a more compact and intuitive format, grouped by country and sorted by year, in attempt to improve readability.
Tidy Data for Plotting: The new
structure_to_plot()function standardizes lists to be printed in the console into tidy data frames, making it easy to feed directly intoggplot2for visualization.
Minor changes
lis_variablesandlws_variablesare now external and documented reference objects in the form of character vectors.It is no longer possible to adjust scale parameters in the
apply_oecd_equivalisation()function.
lissyrtools 0.1.11
Change in lissyuse()
- The output of
lissyuse()now requires explicit assignment to a variable, whereas previously, the function automatically created and assigned a pre-named list (lis_datasetsorlws_datasets) to the global environment.
lissyrtools 0.1.10
Introduction of lissyuse()
- A new and more efficient method for loading data is now available through
lissyuse(). The previous approach, which utilizedread_lissy_files()andmerge_dataset_levels(), will be deprecated moving forward.
Inclusion of sample files
- Inclusion of built-in data frames containing sample files from LIS to assist users in developing LISSY code scripts in local environments.
lissyrtools 0.1.5
Bug fixes
-
transform_equivalise_oecd()and respectivelyimplement_equivalise_oecd()were now corrected for the way they classify children in the argumentvalue_children. Previously this argument was dependent on LIS variablenhhmem17, now it usesnhhmem13.