int3ract

• New generic jn_input(), the extension point of the package, with methods for lm, glm, merMod, sienaFit, matrix, mcmc, mcmc.list, data.frame, sienaBayesFit and multiSiena. Supporting a further model class means writing one jn_input() method returning either jn_wald() (point estimates and covariance) or jn_posterior() (draws); nothing else needs to change. This covers, for instance, models fitted by variational inference, where the variational parameters approximate the posterior.
• JN() returns a classed object with print(), summary(), plot(), autoplot(), as.data.frame(), coef() and vcov() methods. Analyses producing one result per group return a JN_list carrying the same methods. Figures are built on demand by plot() rather than stored in the result.
• JNK_freq() and JNK_bayes() are deprecated. They still work, delegate to JN(), and return the 1.0.x layout, but warn once per session. They will be removed in a future release.

New features

• summary() reports the regions of significance directly: the stretches of the moderator over which each conditional effect is distinguishable from zero, with the share of observations falling inside each. For two-way Wald analyses the boundaries are solved for exactly, so their precision no longer depends on range_size. Also available programmatically as jn_regions().
• plot() attaches data-density panels: a histogram of the observed moderator values below two-way plots, and marginal histograms along both axes of the heatmaps. A region of significance covering moderator values that were hardly observed is the standard failure mode of this technique, and the panels make it visible. Observed values are taken from lm, glm and lme4 models automatically, and can be supplied for any other input through the support argument. Turn the panels off with jn_style(show_density = FALSE).
• New jn_style() collects the colour and pattern settings that were previously repeated across both function signatures.
• plot() draws a figure for every variable involved in the interaction, since each takes its turn as the focal one: two figures for a two-way analysis, three for a three-way one. Pass which for a single figure. It draws and returns invisibly, so nothing is rendered twice.
• New jn_plots() returns every figure of an analysis at once without drawing them, and autoplot() returns a single one; jn_save() writes them to disk, replacing the save and folder arguments.
• Two-way Bayesian analyses can be drawn as a posterior mean with credible band against the moderator (plot(x, type = "band")), directly comparable to the frequentist figure, in addition to the overlaid conditional densities.
• For sienaBayes() results, the level the draws were taken from is now recorded on the result and shown by print(), summary() and the figures: Eta when the parameters involved are shared across groups, Mu when they vary and the hyper-parameter is used. Version 1.0.x labelled the figures this way; the information had been dropped.
• hyper_only = FALSE no longer produces group-level analyses when none of the parameters involved varies between groups. It now reports that and returns the population-level analysis alone, since the group analyses would have been identical copies.

Other changes

• The three-way extension is no longer called the Johnson-Neyman-Krause or JNK technique; it is referred to as JN3.
• The default thresholds for Bayesian analyses are now c(alpha/2, 1 - alpha/2), that is c(0.025, 0.975). The previous default of c(0.49999999999999999, 0.5) marked essentially every cell significant. JNK_bayes() keeps the old default.
• control_fdr is documented as what it is: the Benjamini-Hochberg step-up procedure controlling the false discovery rate across the moderator grid. Earlier documentation described it as Bonferroni-Holm.
• dplyr, tibble, tidyr and scales are no longer dependencies. lme4 moved from Imports to Suggests, since it is needed only for mixed-model input. patchwork was added, for the density panels.
• The package now has a test suite and a Getting started with int3ract vignette.