The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
mmrm
will fail. This is fixed now.Anova
fail. This is fixed now.Anova
is implemented for mmrm
models and available upon loading the car
package. It supports type II and III hypothesis testing.start
for mmrm_control()
is updated to allow better choices of initial values.confint
on mmrm
models will give t-based confidence intervals now, instead of the normal approximation.mmrm_control()
, the allowed vcov
definition is corrected to “Empirical-Jackknife” (CR3), and “Empirical-Bias-Reduced” (CR2).df_md
, it will return statistics with NA
values.method
of mmrm()
now only specifies the method used for the degrees of freedom adjustment.vcov
argument of mmrm()
.model.matrix()
and terms()
methods to assist in post-processing.predict()
method to obtain conditional mean estimates and prediction intervals.simulate()
method to simulate observations from the predictive distribution.residuals()
method to obtain raw, Pearson or normalized residuals.tidy()
, glance()
and augment()
methods to tidy the fit results into summary tables.tidymodels
framework support via a parsnip
interface.covariance
to mmrm()
to allow for easier programmatic access to specifying the model’s covariance structure and to expose covariance customization through the tidymodels
interface.mmrm()
follows the global option na.action
and if it is set other than "na.omit"
an assertion would fail. This is now fixed and hence NA
values are always removed prior to model fitting, independent of the global na.action
option.model.frame()
call on an mmrm
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.mmrm()
always required a data
argument. Now fitting mmrm
can also use environment variables instead of requiring data
argument. (Note that fit_mmrm
is not affected.)emmeans()
failed when using transformed terms or not including the visit variable in the model formula. This is now fixed.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.options(mmrm.max_visits = )
to specify the maximum number of visits allowed in non-interactive mode.free_cores()
in favor of parallelly::availableCores(omit = 1)
.model.frame()
method has been updated: The full
argument is deprecated and the include
argument can be used instead; by default all relevant variables are returned. Furthermore, it returns a data.frame
the size of the number of observations utilized in the model for all combinations of the include
argument when na.action= "na.omit"
.component(., "optimizer")
instead of previously attr(., "optimizer")
.mmrm
function call with argument method
. Options are “Kenward-Roger”, “Kenward-Roger-Linear” and “Satterthwaite” (which is still the default). Subsequent methods calls will respect this initial choice, e.g. vcov(fit)
will return the adjusted coefficients covariance matrix if a Kenward-Roger method has been used.mmrm
arguments to allow users more fine-grained control, e.g. mmrm(..., start = start, optimizer = c("BFGS", "nlminb"))
to set the starting values for the variance estimates and to choose the available optimizers. These arguments will be passed to the new function mmrm_control
.drop_visit_levels
to allow users to keep all levels in visits, even when they are not observed in the data. Dropping unobserved levels was done silently previously, and now a message will be given. See ?mmrm_control
for more details.mmrm
calls, the weights
object in the environment where the formula is defined was replaced by the weights
used internally. Now this behavior is removed and your variable weights
e.g. in the global environment will no longer be replaced.free_cores()
in favor of parallelly::availableCores(omit = 1)
.optimizer = "automatic"
in favor of not specifying the optimizer
. By default, all remaining optimizers will be tried if the first optimizer fails to reach convergence.emmeans
package for computing estimated marginal means (also called least-square means) for the coefficients.summary
, logLik
, etc.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.
Health stats visible at Monitor.