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Changelog

Source: NEWS.md

dyadMLM (development version)

dyadMLM 0.2.0

CRAN release: 2026-08-21

  • This early API-stabilization release intentionally makes a few direct, breaking changes from 0.1.0. Compatibility wrappers are not retained.

  • Retained generated columns now use a single leading dot instead of .dy_ for more readable model formulas. For example, .dy_x_actor becomes .x_actor. The .dy_ prefix is reserved for temporary implementation columns.

  • prepare_dyad_data() now uses compact composition-column names when the final data contain one composition, such as .is_female and .member_contrast_arbitrary. Set short_colnames = FALSE to retain composition-qualified names. recover_exchangeable_covariance() recognizes both forms.

  • prepare_dyad_data(include_arbitrary_member_contrast = TRUE) can now add arbitrary member contrasts for distinguishable compositions without changing their metadata or role indicators. This supports full and exchangeability-constrained APIMs from the same prepared data. set_exchangeable_compositions still performs reclassification for pooling and DIM preparation.

  • Added a summary() method for prepared data that prints the dyadic structure followed by standard summaries of all columns.

  • Printing prepared data now uses current dyad and composition counts. If a required column has been removed, the unavailable summary is identified instead of displaying its preparation-time count.

  • Generated-column tracking now records all retained composition and modeling columns. Printing and model comparison use these records rather than inferring column ownership from a prefix, and generated names are checked for collisions and valid R syntax before they are written.

  • prepare_dyad_data(add_apim_gmc_predictors = TRUE) now adds GMC source, actor, and partner columns alongside raw APIM columns, plus lagged variants when requested. It uses one mean over retained non-missing values, warns about skipped non-numeric predictors in mixed selections, and leaves DIM/DSM centering unchanged.

  • For longitudinal data, prepare_dyad_data() now temporarily adds an all-missing partner row when only one member is present at an observed dyad-occasion. This preserves partner CBP values and exact source-occasion APIM, DIM, and DSM lags. Temporary rows are removed before the prepared data are returned. This is structural completion for column construction, not imputation or the addition of analysis rows.

  • Numeric structural columns and numeric predictors selected for preparation now reject Inf and -Inf before model-ready columns are generated. Errors identify the affected columns and input rows; NA and NaN remain supported as missing predictor values.

  • Renamed compare_nested_glmmTMB_models() to compare_nested_models(). Its printed conclusion now uses a configurable alpha level and no longer recommends a model solely because the likelihood-ratio test is not significant.

  • recover_exchangeable_covariance() now returns an exchangeable_covariance object instead of an exchangeable_rescov object, with a clearer member-level print heading.

  • For brms models, recover_exchangeable_covariance() now returns posterior- mean matrices by default. Use posterior = "median" or "draws" for the corresponding alternatives.

  • Added package-level help at ?dyadMLM, with links to the main functions, example datasets, and getting-started documentation.

  • Example datasets no longer include the redundant dyad_composition column. Instead, dyads_ild now includes member-specific AR(1) residual processes.

dyadMLM 0.1.0

CRAN release: 2026-07-30

  • Initial release.
  • Cleaned up the pre-release public API with these direct migration mappings: group to dyad, lag_predictors to lag1_predictors, model_type to model_types, temporal_predictor_decomposition to temporal_decomposition, "time_2l" to "2l", include_compositions to keep_compositions, compare_dyad_models() to compare_nested_glmmTMB_models(), exchangeable_rescov() to recover_exchangeable_covariance(), pairs to block_pairings, pairing fields shared and difference to shared_block and difference_block, and print argument what to representation.
  • Renamed generated exchangeable-member contrasts from .dy_diff_{composition}_arbitrary to .dy_member_contrast_{composition}_arbitrary.
  • Renamed the package from interdep to dyadMLM. Package-generated columns now use the .dy_ prefix instead of .i_.
  • Added validation and preparation of cross-sectional and intensive longitudinal dyadic data with distinguishable, exchangeable, and mixed dyad compositions.
  • Added composition filtering, exchangeability overrides, and pooling.
  • Exchangeable-dyad difference columns now use an _arbitrary suffix.
  • Added temporal predictor decomposition and model-ready columns for APIM, DIM, and DSM parameterizations.
  • Added compare_nested_glmmTMB_models() for compatible nested glmmTMB models and recover_exchangeable_covariance() for back-transforming shared/difference random-effect covariance structures.
  • Added example datasets, getting-started and model-specific vignettes, and a concise print method for prepared data.