NEWS.md
In brmsmargins: Bayesian Marginal Effects for 'brms' Models

brmsmargins 0.2.0

Fixed a bug when using prediction() with option effects = "integrateoutRE" when smooth terms were present. As prediction() underpins other functions, such as brmsmargins() this issue also impacts those other functions.
New function: marginalcoef() which calculates population averaged (marginal) coefficients for the fixed effects coefficients from mixed effects models using a method described by Donald Hedeker, who joins the author team. Currently, only the main location parameter is supported. That is, marginal coefficients for the scale part of a model, in location and scale models, is not currently supported.
New argument, wat, added to brmsmargins() to support including calculating average marginal effects for multilevel centered categorical predictors.
Updates to vignettes demonstrating: (1) the use of marginal coefficients; (2) marginal effects for centered categorical predictors; and (3) 'simple' marginal effects when models include interaction terms.
Revised documentation for bmrsmargins() and prediction() to be clearer around which arguments users must directly specify and which are optional or have sensible defaults.
Added more unit testing and vignettes.

Fixed a bug preventing predictions integrating out random effects for mixed effects models with a random intercept only (reported in Issue#1). Thanks to @ajnafa for reporting.
Added support for Gamma and Beta regression models.
More extensive testing added.