v0.3.6
New Features
- The argument
method
ofmmrm()
now only specifies the method used for the
degrees of freedom adjustment. - Add empirical, empirical Jackknife and empirical bias-reduced adjusted coefficients
covariance estimates, which can be specified via the newvcov
argument ofmmrm()
. - Add residual and between-within degrees of freedom methods.
- Add Kenward-Roger support for spatial covariance structures.
- Add
model.matrix()
andterms()
methods to assist in post-processing. - Add
predict()
method to obtain conditional mean estimates and prediction intervals. - Add
simulate()
method to simulate observations from the predictive distribution. - Add
residuals()
method to obtain raw, Pearson or normalized residuals. - Add
tidy()
,glance()
andaugment()
methods to tidy the fit results into summary tables. - Add
tidymodels
framework support via aparsnip
interface. - Add argument
covariance
tommrm()
to allow for easier programmatic access
to specifying the model's covariance structure and to expose covariance
customization through thetidymodels
interface.
Bug Fixes
- Previously
mmrm()
follows the global optionna.action
and if it is set
other than"na.omit"
an assertion would fail. This is now fixed and henceNA
values are always removed prior to model fitting, independent of the global
na.action
option. - Previously a
model.frame()
call on anmmrm
object with transformed terms, or new
data, e.g.model.frame(mmrm(Y ~ log(X) + ar1(VISIT|ID), data = new_data)
,
would fail. This is now fixed. - Previously
mmrm()
always required adata
argument. Now fittingmmrm
can also use
environment variables instead of requiringdata
argument. (Note that
fit_mmrm
is not affected.) - Previously
emmeans()
failed when using transformed terms or not including the visit
variable in the model formula. This is now fixed. - Previously
mmrm()
might provide non-finite values in the Jacobian calculations,
leading to errors in the Satterthwaite degrees of freedom calculations. This will raise
an error now and thus alert the user that the model fit was not successful.
Miscellaneous
- Use automatic differentiation to calculate Satterthwaite adjusted degrees of freedom,
resulting in 10-fold speed-up of the Satterthwaite calculations after the initial model fit. - Add an interactive confirmation step if the number of visit levels is too large
for non-spatial covariance structures. Useoptions(mmrm.max_visits = )
to specify the
maximum number of visits allowed in non-interactive mode. - Removed
free_cores()
in favor ofparallelly::availableCores(omit = 1)
. - The
model.frame()
method has been updated: Thefull
argument is deprecated and
theinclude
argument can be used instead; by default all relevant variables are
returned. Furthermore, it returns adata.frame
the size of the number of observations
utilized in the model for all combinations of theinclude
argument
whenna.action= "na.omit"
. - Overall, seven vignettes have been added to the package. All vignettes have a slightly
different look now to reduce the size of the overall R package on CRAN. - The used optimizer is now available via
component(., "optimizer")
instead of previously
attr(., "optimizer")
.
Full Changelog: v0.2.2...v0.3.6