First version submitted to CRAN.
plot_networks_by_group() restores par()
with an immediate on.exit() call and always closes its
temporary device; the NetPowerLab app restores the user’s
par() after the plot.
The SemPowerLab application (run_sempowerlab()),
added during development, moved to the PsyMetricTools package, which
covers latent variable models. semPower is no longer
suggested.
run_netpowerlab(): launches the NetPowerLab Shiny
application, which plans the sample size of a network study by wrapping
bootnet::netSimulator() and
powerly::powerly(). The reference network is built block by
block (one block per instrument) and acts as the effect size; the app
also writes the reproducible script and a draft of the Participants
section. shiny, bslib and powerly
moved into Suggests.sample_size_EGA_montecarlo(), with
sample_size_EGA_control(),
make_likert_thresholds(),
plot_sample_size_EGA_montecarlo(),
plot_power_curve_ci(),
plot_failure_decomposition(),
show_recommendation() and show_plots(): a
priori sample size for EGA through Monte Carlo simulation.sample_size_EGA_control() merged nested lists:
control = list(targets = list(ari = .80)) silently kept the
default edge_correlation target. Entries now replace the
defaults.sample_size_EGA_montecarlo(): items that EGA leaves
without a community no longer inflate the ARI; bootstrap resamples that
never reach the target are treated as censored instead of dropped, so
the upper CI bound is no longer understated; the bootstrap CI is
reproducible with parallel = TRUE; a non positive definite
partial network stops with a message that gives the admissible edge
weight; the sensitivity sweep skips the edge-threshold runs when no
target depends on them and compares every row with the main run.optimize_leiden_resolution() treated untested
resolutions (after an early stop) as having TEFI = 0, could choose one
of them as the best, and misaligned the models with their rows in
comparison when a resolution failed.plot_lvm() labelled residual correlations as residual
partial correlations, and did not restore the graphical parameters.plot_latent_network_diagram() called
getmatrix() without importing it, so psychonetrics models
failed unless psychonetrics was attached.compute_netScores() wrote to the global environment
when the stability step failed.convert_EGA_to_df() returned NA as the
algorithm for EGAnet 2.x results.mgm_error_metrics() passed levels instead
of level to mgm::mgm().print methods for silent_gg and
silent_plot are now registered by the package.plot_latent_network_diagram() requires
output_path.message() instead of
cat(), and compute_netScores() only asks for
dimension names in interactive sessions.boot_and_evaluate(),
refine_items_by_stability() and
compute_netScores() default to seed = NULL;
the user’s future plan is restored on exit; parallel
defaults use at most 2 cores.reshape2 and stringr are no longer needed;
viridis moved to Suggests; psychonetrics added
to Suggests. Requires R >= 4.1.0.