  The brms package allows R users to easily specify a wide range of Bayesian
single-level and multilevel models, which are fitted with the probabilistic
programming language Stan behind the scenes. Several response distributions are
supported, of which all parameters (e.g., location, scale, and shape) can be
predicted at the same time thus allowing for distributional regression.
Non-linear relationships may be specified using non-linear predictor terms or
semi-parametric approaches such as splines or Gaussian processes. To make all
of these modeling options possible in a multilevel framework, brms provides an
intuitive and powerful formula syntax, which extends the well known formula
syntax of lme4. The purpose of the present paper is to introduce this syntax in
detail and to demonstrate its usefulness with four examples, each showing other
relevant aspects of the syntax.
