# make_standata

##### Data for brms Models

Generate data for brms models to be passed to Stan

##### Usage

```
make_standata(formula, data, family = gaussian(), prior = NULL,
autocor = NULL, nonlinear = NULL, cov_ranef = NULL,
sample_prior = c("no", "yes", "only"), knots = NULL, control = list(),
...)
```

##### Arguments

- formula
An object of class

`formula`

or`brmsformula`

(or one that can be coerced to that classes): A symbolic description of the model to be fitted. The details of model specification are explained in`brmsformula`

.- data
An object of class

`data.frame`

(or one that can be coerced to that class) containing data of all variables used in the model.- family
A description of the response distribution and link function to be used in the model. This can be a family function, a call to a family function or a character string naming the family. Every family function has a

`link`

argument allowing to specify the link function to be applied on the response variable. If not specified, default links are used. For details of supported families see`brmsfamily`

. By default, a linear`gaussian`

model is applied.- prior
One or more

`brmsprior`

objects created by`set_prior`

or related functions and combined using the`c`

method. A single`brmsprior`

object may be passed without`c()`

surrounding it. See also`get_prior`

for more help.- autocor
An optional

`cor_brms`

object describing the correlation structure within the response variable (i.e., the 'autocorrelation'). See the documentation of`cor_brms`

for a description of the available correlation structures. Defaults to`NULL`

, corresponding to no correlations.- nonlinear
(Deprecated) An optional list of formulas, specifying linear models for non-linear parameters. If

`NULL`

(the default)`formula`

is treated as an ordinary formula. If not`NULL`

,`formula`

is treated as a non-linear model and`nonlinear`

should contain a formula for each non-linear parameter, which has the parameter on the left hand side and its linear predictor on the right hand side. Alternatively, it can be a single formula with all non-linear parameters on the left hand side (separated by a`+`

) and a common linear predictor on the right hand side. As of brms 1.4.0, we recommend specifying non-linear parameters directly within`formula`

.- cov_ranef
A list of matrices that are proportional to the (within) covariance structure of the group-level effects. The names of the matrices should correspond to columns in

`data`

that are used as grouping factors. All levels of the grouping factor should appear as rownames of the corresponding matrix. This argument can be used, among others to model pedigrees and phylogenetic effects. See`vignette("brms_phylogenetics")`

for more details.- sample_prior
Indicate if samples from all specified proper priors should be drawn additionally to the posterior samples (defaults to

`"no"`

). Among others, these samples can be used to calculate Bayes factors for point hypotheses. If set to`"only"`

, samples are drawn solely from the priors ignoring the likelihood. In this case, all parameters must have proper priors.- knots
Optional list containing user specified knot values to be used for basis construction of smoothing terms. See

`gamm`

for more details.- control
A named list currently for internal usage only

- ...
Other potential arguments

##### Value

A named list of objects containing the required data to fit a brms model with Stan.

##### Examples

```
# NOT RUN {
data1 <- make_standata(rating ~ treat + period + carry + (1|subject),
data = inhaler, family = "cumulative")
names(data1)
data2 <- make_standata(count ~ log_Age_c + log_Base4_c * Trt_c
+ (1|patient) + (1|visit),
data = epilepsy, family = "poisson")
names(data2)
# }
```

*Documentation reproduced from package brms, version 1.10.2, License: GPL (>= 3)*