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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.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.