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In {modelbased}, testing complex hypotheses is now even more flexible: `estimate_contrasts()` now supports `comparison = "omnibus"`, allowing you to easily calculate a global omnibus test for differences between levels of a predictor. 📊 (2/4) easystats.github.io/modelbased/
{performance} brings powerful new tools for your model diagnostics: The new `check_priors()` function allows you to conduct prior predictive checks for Bayesian models, helping you better validate your model assumptions. 🔍 (3/4) easystats.github.io/performance/
And the rest of the family is joining in: {parameters} now supports lavaan objects, {see} adds new plot methods, and {insight} delivers a major performance boost when processing large, nested list objects. 🚀 easystats.github.io/see/ easystats.github.io/parameters/ easystats.github.io/insight/
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