NEWS.md
In InterconectaR: Psychological Network Analysis and Psychometric Insights

InterconectaR 1.0.1

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.

New 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.
New 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.

NetPowerLab ran powerly with an increasing curve for specificity, which falls as N grows. It now reports a recommendation only when powerly converged and the value is not at the top of the range, and the script and paragraph follow the network and settings actually simulated.
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().

No function assigns into the global environment: the print methods for silent_gg and silent_plot are now registered by the package.
Nothing is written to disk by default: plot_latent_network_diagram() requires output_path.
Functions report progress with message() instead of cat(), and compute_netScores() only asks for dimension names in interactive sessions.
No fixed seeds inside functions: 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.
Every exported function documents its return value and has a runnable example.
reshape2 and stringr are no longer needed; viridis moved to Suggests; psychonetrics added to Suggests. Requires R >= 4.1.0.

InterconectaR 1.0.0

Initial release (GitHub only).
40 functions for network analysis and psychometric modeling.
Tools for centrality calculation, bridge metrics, and community structure visualization.
Support for group network comparison and Mixed Graphical Models (MGM).
Exploratory Graph Analysis (EGA) integration via EGAnet.
Bootstrap evaluation of network estimation algorithms.
Advanced visualization functions for network plots with R2 rings, Cleveland dot plots, and bullet charts.