Changelog • mwana

mwana 0.2.2

Added new functions:
- mw_stattest_ageratio2(): Tests for statistical differences in proportions as in mw_stattest_ageratio(), but for cases where age is provided in the categories “6–23” and “24–59” months.
- mw_estimate_prevalence_screening2(): Estimates the prevalence of acute malnutrition for non-survey data when age is given in the categories “6–23” and “24–59” months. This ensures that the age-weighting approach is applied when applicable. Outliers are excluded using raw MUAC rather than MUAC-for-age z-scores.

Resolved an issue with mw_check_ipcamn_ssreq(), which was previously not returning the correct statistics for grouped analysis.

Refactored plausibility check and prevalence functions to allow multiple grouping variables (rather than just one, as was the case in earlier versions). The .by argument is no longer used; instead, users must specify the variable or set of variables using ... .
Reduced repeated code in several function definitions.

Updated documentation in README, data documentation function documentation, and vignettes to improve grammar, coherence, and consistency;
Enforced use of :: to state external package dependencies;
Ensured that a code sequence started with a function statement rather than a data.frame piped into a function;
simplified specific code syntax

Added new function mw_estimate_prevalence_screening() to estimate prevalence of wasting by MUAC from non survey data: screenings, sentinel sites, etc.

Resolved issues with mw_neat_output_mfaz(), mw_neat_output_wfhz() and mw_neat_output_muac() not returning neat and tidy output for grouped data.frame from their respective plausibility checkers.
Resolved issue with edema argument in prevalence functions that was not working as expected when set to NULL.