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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;
    1. marginal effects for centered categorical predictors; and
    2. ‘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

CRAN release: 2021-12-16

  • 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