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nparLD 2.3.0
Major redesign
- 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 = ...).
Interface changes
- 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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.