pecanr 0.2.0

New features

eta2p() and batch_eta2p() now support design = "mixed" for models with both crossed and nested random effects simultaneously. A canonical example is participants viewing multiple photos of each model: photos are nested within models, but both levels are crossed with participants. Supply both cross_vars and nest_vars to use this design.

Fixed a bug in operative effect size calculation for crossed designs. detect_within_between() previously used hardcoded $subj and $item keys to classify grouping factors as within or between, which caused intercept variances to be silently omitted from the operative denominator. Keys are now indexed by actual variable name, so the correct components are always included.

batch_eta2p() output columns for within/between status are now named within_<varname> (e.g., within_participant, within_item) rather than the hardcoded within_subj and within_item. Code that references these columns by name will need to be updated.
Operative effect sizes with 3 or more crossed factors now correctly gate each factor’s intercept variance on its within/between status. Previously, third and higher factors were always included in the operative denominator regardless of whether the effect was within or between those factors.

Initial CRAN release.
eta2p() computes partial eta-squared for a single fixed effect in a fitted lmer model, supporting crossed and nested random effects structures.
batch_eta2p() computes partial eta-squared for all fixed effects in a model.
Crossed designs support any number of grouping factors via cross_vars.
Nested designs support automatic effect-level detection.
Operative effect sizes available via operative = TRUE.
Random slope variances are translated to the outcome scale using σ²_slope × σ²_X, correctly accounting for predictor scaling and interaction terms.