brmsmargins 0.2.1

• Added seed argument to marginalcoef() to allow for reproducible results.
• Minor documentation edits.

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.

brmsmargins 0.1.1

• 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.

brmsmargins 0.1.0

• Initial release