cat2cat 0.6.1

This release incorporates feedback from the PhD dissertation reviewers: dr hab. Andrzej Dudek, dr hab. Joanna Landmesser-Rusek, and dr hab. Paweł Andrzej Strzelecki.

New features

• New occup_panel dataset - a rotational panel covering 2009Q1–2010Q4 - used to illustrate id_var direct matching and to exercise the panel-data code path in tests.
• Naive Bayes ("nb") added to the supported ML methods, via e1071 (Suggests).
• summary_c2c() now supports both lm and glm, adds input/shape validation (df_old/df_new, coefficient table checks), and reports the reference distribution used for p-values (t or normal). Added edge-case tests and aligned regression/panel vignette examples with current summary_c2c() output and fixed-effects inference guidance.
• cat2cat_ml_run() now reports the Brier score and mean P(true class) in addition to accuracy. A proper scoring rule matters because cat2cat weights are probabilities, not classifications - a model can be accurate and still be poorly calibrated.
• All stopifnot() assertions now carry descriptive messages, so failures point the user at the offending argument instead of printing the raw expression.
• cat2cat() ML fallback is now configurable via ml$on_fail ("freq", "naive", "na", "error") with optional warning control via ml$fail_warn. Failed ML weights are now explicitly handled according to this policy instead of always silently falling back to frequency weights.
• cat2cat() ML now accepts factor features in addition to numeric/logical: factor columns listed in ml$features are automatically one-hot encoded using the union of levels observed in ml$data and the target period.

Documentation

• Vignettes reorganised into three clearer guides: Get Started, Choosing Weights and Validating ML, and Advanced Workflows. The goal is a cleaner reader path: core concepts first, method choice second, advanced workflows third.
• Get Started now focuses on the two-period workflow, core assumptions, and the value added of cat2cat for group-level longitudinal analysis, with sharper pointers to the more advanced guides.
• Choosing Weights and Validating ML is now structured as a decision guide: understanding weight assumptions, checking robustness across methods, validating ML against naive/frequency baselines, and handling failed ML predictions.
• Advanced Workflows now collects ML setup, multi-period chaining, rotational panels with id_var, aggregated-data workflows, hierarchical-code mappings, and regression/inference after harmonisation into one better-structured advanced reference.
• Added a When cat2cat won’t help section distinguishing hard blockers (no mapping table, unobserved category) from method-specific limitations with available workarounds.
• Corrected the \(R^2\) guidance: ordinary \(R^2\) is preserved in neutral replication cases when replicated copies keep the same response/covariates and weights sum back to the source observation; adjusted \(R^2\), AIC, and BIC require original-scale degrees-of-freedom care, and fit statistics with harmonised-category covariates are conditional on the chosen weights.
• Roxygen for cat2cat() and cat2cat_agg() trimmed - argument documentation kept, conceptual material moved to the vignettes where it belongs.

Bug fixes

• Fixed the nomnoml diagram that previously mislabelled the base/target sides under forward mapping.
• Fixed get_freqs() for r-devel/R CMD check: replaced as.data.frame(table(...)) conversion with direct data.frame(input = names(tab), Freq = as.integer(tab)) construction to avoid failures when NA appears in table names (row names contain missing values).

cat2cat 0.4.7

• New cat2cat_ml_run function to check the ml models performance before cat2cat with ml option is run. Now, the ml models are more transparent.
• Add tests for cat2cat related journal (softwarex) paper.
• Add CITATION file.
• Internal changes to make the code base more clear.
• Replace itemize with describe in the latex documentation.

cat2cat 0.4.6

• Add some ropensci standards, like CONTRIBUTING file and testthat version 3.
• Add LICENSE file.
• Update DESCRIPTION file.
• Update outdated URLs.
• cat2cat_agg has updated cat_var argument to two new ones, cat_var_old and cat_var_new.
• Rename the master to main branch.
• Improve tests and lintr related issues.

cat2cat 0.4.5

• The freqs_df argument in the cat2cat function is moved from data to mappings part, it is backward compatible. Now it is consistent with the python cat2cat implementation.
• pkgcheck related fixes, like 80 chars per line.
• Improve data and library calls style.

cat2cat 0.4.4

• Fix example in the cat2cat function.
• Improve documentation.
• Improve validation.

cat2cat 0.4.3

• Fix dummy_c2c to be backward compatible.
• Add more tests for base utils functions.
• Improve cat_apply_freq function performance.
• Improve documentation.
• Improve validation.

cat2cat 0.4.2

• The ml argument in the dummy_c2c function is redefined, shorter names for a simpler usage.
• The cat2cat ml part is using direct cat_var for target (for an update) dataset now, not the one from the ml argument list.
• Improve procedure graphs.

cat2cat 0.4.1

• additional cat2cat validation, if the trans table covers all needed levels.
• documentation and tests improvements.

cat2cat 0.4.0

• new syntax of the ml and data argument in the cat2cat::cat2cat function, two additional arguments each.
• prune_c2c scales the weights now, so still sum to one for each subject.
• new function dummy_c2c to add a default cat2cat columns to a data.frame.
• occupand occup_small datasets have 4 periods now.
• add the 4 periods example to the vignette.
• custom pkgdown reference.

cat2cat 0.3.3

• improve the pkgdown website.
• deparse instead of deparse1.

cat2cat 0.3.2

• tinyverse world, even less dependencies.

cat2cat 0.3.1

• updated README file.
• improved covr and tests.
• updated vignette.

cat2cat 0.3.0

• fixed the cat2cat function, the ml part is assuming that categorical variable is always named “code”.
• fixed problems when using only one feature in the ml part of cat2cat function.
• persist NA values in a categorical variable in the cat2cat function.
• updated vignette.
• improved roxygen2 docs.
• transferred caret and randomForest packages to Suggests, they are delayed loaded now.
• styler of the code.
• more readable code.
• removed data.table from Imports.

cat2cat 0.2.1

• usage of summary_c2c with the default df_new argument.
• plot_c2c roxygen2

cat2cat 0.2.0

• plot_c2c

cat2cat 0.1.9

• vignette improvements

cat2cat 0.1.8

• pt inside summary_c2c
• VignetteIndexEntry

cat2cat 0.1.7

• URL for doi in vignettes

cat2cat 0.1.6

• basic vignette
• rm .internal.selfref attr for mapped df
• assertthat instead of stopifnot

cat2cat 0.1.5

• data.R adding set.seed
• lack of a one bracket in description file

cat2cat 0.1.4

• remove the unnecessary imports in the DESCRIPTION file

cat2cat 0.1.3

• Title reduce to less than 65 characters.
• doi of journal paper added to a description section in the DESCRIPTION file.
• unnecessary dontrun in data.R were removed.

cat2cat 0.1.2

• occup_small dataset to pass checks in terms of computation time of examples.
• data.table rbindlist.
• optimize for loop for ml models.

cat2cat 0.1.1

• Title format in Description file.
• spelling.

cat2cat 0.1.0

• More ml methods for cat2cat function - “knn”, “rf”, “lda”.
• prune_c2c and cross_c2c to improve processing of results.
• Enable cat2cat for panel with unique identifier.
• Turn on github actions - covr, pkgdown, check.
• Preparation before R CRAN.