Changes in version 0.4.0
This version substantially improves the simulate
method.
New features
- The simulate method is now much more flexible. New features include:
- Compare more than 2 model formulas (#2).
- Apply a data transformation during simulation;
sim_formula(..., data_transform = func)
.
As an exampletransform_to_posttest
is included. - Choose which parameters to test;
sim_formula(..., test = "treatment")
- Fit OLS models. If a model formula is supplied that contain no random effects the
model is fit using OLSlm()
. If this is combined with thetransform_to_posttest
the
longitudinal model can be compared to a cross-sectional model, e.g. ANCOVA. - Investigate LRT model selection of the random effects. Nested random effect models
can be tested using LRT, and results from the "best" model is returned. The log-likelihood
is saved during each simulation, so the model selection can be done as a
post-processing step;summary.plcp_sim(..., model_selection = "FW", LRT_alpha = 0.25)
.
Breaking canges
simulate(formula = x)
must now be created using the new functionssim_formula
, or
sim_formula_compare
, and can no longer be a named list or a character vector.
Bug fixes
summary.plcp_sim()
now show fixed effecttheta
s in the correct order, thanks to
GitHub user Johnzav888 (#10).