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;
- marginal effects for centered categorical predictors; and
- ‘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