# brmsmargins 0.3.0
* Now supports response variables with a binomial distribution.
  Predictions that marginalise over random effects will use the number of trials.
  For contrasts, such as using `brmsmargins()` you can use the `at =` argument to
  force trials to 1 to get marginal probabilities rather than counts of successful
  trials.
* Experimental support for integrating out random effects from a student t distribution.
  Currently only supports this for location parameters. When `dpar` is not
  empty in `brms` only Gaussian distributions are supported. Some caution is
  needed here as `brms` uses the same degree of freedom parameter for all random
  effects of the same grouping variable, so for complex random effect structures,
  there may be errors in how they are integrated out.

# 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
