# dyadMLM 0.1.0

* 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`. Covariance recovery continues
  to recognize legacy contrast names in previously fitted models.
* 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.
