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.