NEWS

nparLD 2.3.0 (2026-08-22)

Added a general formula interface for crossed factorial longitudinal designs.
Added inference for hypotheses in marginal distribution functions (hypothesis = "H0F") and unweighted relative marginal effects (hypothesis = "H0p").
Added support for missing observations.
Added support for dependent replicate measurements via the replicate argument.
Added subject-level and observation-level cell weighting for relative marginal effects.
Added multiple contrast procedures and simultaneous confidence intervals.
Added rank- and pseudo-rank-based inference through a unified interface.
Added the argument covariance, which optionally includes the estimated covariance matrix in the output.
Added updated documentation, examples, README, vignette, and example datasets.
Added the brdu data set for illustrating dependent replicate measurements.
Added term-specific plots of factor-information estimates and confidence intervals via plot(fit, term = ...).

Factor ordering is now controlled through ordinary R factor levels before calling nparLD().
Earlier design-specific ordering arguments are no longer part of the main interface.
Classical designs such as LD-F1, F1-LD-F1, LD-F2, F1-LD-F2, and F2-LD-F1 are now specified through the formula interface.