diff --git a/DESCRIPTION b/DESCRIPTION
index 80d7542a..ab87fc9a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: bmm
 Title: Easy and Accesible Bayesian Measurement Models using 'brms'
-Version: 0.4.0.9000
+Version: 0.4.1.9000
 Authors@R: c(
     person("Vencislav", "Popov", , "vencislav.popov@gmail.com", role = c("aut", "cre", "cph")),
     person("Gidon", "Frischkorn", , "gidon.frischkorn@psychologie.uzh.ch", role = c("aut", "cph")),
diff --git a/NAMESPACE b/NAMESPACE
index 9e8546cd..4d3b8c73 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -3,6 +3,9 @@
 S3method("+",bmmformula)
 S3method("[",bmmformula)
 S3method(bmf2bf,bmmmodel)
+S3method(brms::get_prior,bmmformula)
+S3method(brms::make_stancode,bmmformula)
+S3method(brms::make_standata,bmmformula)
 S3method(check_data,IMMspatial)
 S3method(check_data,bmmmodel)
 S3method(check_data,default)
@@ -58,9 +61,9 @@ export(fit_info)
 export(fit_model)
 export(get_model_prior)
 export(get_stancode)
-export(get_stancode_parblock)
 export(get_standata)
 export(k2sd)
+export(make_stancode_parblock)
 export(mixture2p)
 export(mixture3p)
 export(pIMM)
diff --git a/NEWS.md b/NEWS.md
index 94b3c819..10036eba 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,8 @@
 # bmm 0.4.0+
 
+### New features
+* deprecate get_model_prior(), get_stancode() and get_standata(). These functions will be removed in future versions of the package. If you are using *brms* version 2.20.14 or later, you can now use the *brms* functions `get_prior`, `make_stancode` and `make_standata` directly with *bmm* models.
+
 # bmm 0.4.0
 
 ### New features
diff --git a/R/helpers-data.R b/R/helpers-data.R
index 43f32791..381239aa 100644
--- a/R/helpers-data.R
+++ b/R/helpers-data.R
@@ -230,20 +230,14 @@ rad2deg <- function(rad){
 #'   with `bmm`. Given the `model`, the `data` and the `formula` for the model,
 #'   this function will return the combined stan data generated by `bmm` and
 #'   `brms`
-#' @param formula An object of class `brmsformula`. A symbolic description of
-#'   the model to be fitted.
-#' @param data An object of class data.frame, containing data of all variables
-#'   used in the model. The names of the variables must match the variable names
-#'   passed to the `bmmmodel` object for required argurments.
-#' @param model A description of the model to be fitted. This is a call to a
-#'   `bmmmodel` such as `mixture3p()` function. Every model function has a
-#'   number of required arguments which need to be specified within the function
-#'   call. Call [supported_models()] to see the list of supported models and
-#'   their required arguments
-#' @param prior One or more `brmsprior` objects created by [brms::set_prior()]
-#'   or related functions and combined using the c method or the + operator. See
-#'   also [get_model_prior()] for more help. Not necessary for the default model
-#'   fitting, but you can provide prior constraints to model parameters
+#'
+#'   If you are using *brms* version 2.20.14 or later, you can use
+#'   [make_standata()] directly with the `bmmformula` object. If you are using
+#'   an older version of *brms*, you have to use [get_standata()] to obtain the
+#'   default priors. The usage of [get_standata()] is deprecated and will be
+#'   removed in future versions of *bmm*.
+#'
+#' @inheritParams fit_model
 #' @param ... Further arguments passed to [brms::make_standata()]. See the
 #'   description of [brms::make_standata()] for more details
 #'
@@ -266,15 +260,32 @@ rad2deg <- function(rad){
 #' ff <- bmf(c ~ 1,
 #'           kappa ~ 1)
 #'
-#' # fit the model
-#' get_standata(formula = ff,
-#'              data = dat,
-#'              model = sdmSimple(resp_err = "y")
-#' )
+#'
+#' if (utils::packageVersion('brms') >= "2.20.14") {
+#'   # generate the stan data (if using brms version 2.20.14 or later)
+#'   make_standata(formula = ff,
+#'                 data = dat,
+#'                 model = sdmSimple(resp_err = "y"))
+#' } else {
+#'   # generate the stan data (if using an older version of brms)
+#'   get_standata(formula = ff,
+#'                data = dat,
+#'                model = sdmSimple(resp_err = "y"))
+#' }
 #' }
 #'
 get_standata <- function(formula, data, model, prior=NULL, ...) {
+  if (utils::packageVersion('brms') >= "2.20.14") {
+    message("get_standata is deprecated. Please use make_standata() instead.")
+    return(brms::make_standata(formula = formula, data = data,
+                               model = model, prior = prior, ...))
+  }
+  make_standata.bmmformula(formula = formula, data = data,
+                           model = model, prior = prior, ...)
+}
 
+#' @rdname get_standata
+make_standata.bmmformula <- function(formula, data, model, prior = NULL, ...) {
   # check model, formula and data, and transform data if necessary
   model <- check_model(model, data)
   data <- check_data(model, data, formula)
diff --git a/R/helpers-model.R b/R/helpers-model.R
index fc94de4d..9a0e6a24 100644
--- a/R/helpers-model.R
+++ b/R/helpers-model.R
@@ -605,36 +605,27 @@ use_model_template <- function(model_name,
 
 
 #' @title Generate Stan code for bmm models
-#' @description A wrapper around `brms::make_stancode()` for models specified with
-#'   `bmm`. Given the `model`, the `data` and the `formula` for the model, this
-#'   function will return the combined stan code generated by `bmm` and `brms`
-#' @param formula An object of class `bmmformula`. A symbolic description of
-#'   the model to be fitted.
-#' @param data An object of class data.frame, containing data of all variables
-#'   used in the model. The names of the variables must match the variable names
-#'   passed to the `bmmmodel` object for required argurments.
-#' @param model A description of the model to be fitted. This is a call to a
-#'   `bmmmodel` such as `mixture3p()` function. Every model function has a
-#'   number of required arguments which need to be specified within the function
-#'   call. Call [supported_models()] to see the list of supported models and
-#'   their required arguments
-#' @param prior One or more `brmsprior` objects created by [brms::set_prior()]
-#'   or related functions and combined using the c method or the + operator. See
-#'   also [get_model_prior()] for more help. Not necessary for the default model
-#'   fitting, but you can provide prior constraints to model parameters
+#' @description A wrapper around `brms::make_stancode()` for models specified
+#'   with `bmm`. Given the `model`, the `data` and the `formula` for the model,
+#'   this function will return the combined stan code generated by `bmm` and
+#'   `brms`
+#'
+#'   If you are using *brms* version 2.20.14 or later, you should use
+#'   [make_stancode()] directly with the `bmmformula` object. If you are using
+#'   an older version of *brms*, you have to use [get_stancode()] to obtain the
+#'   default priors. The usage of [get_stancode()] is deprecated and will be
+#'   removed in future versions of *bmm*.
+#'
+#' @inheritParams fit_model
 #' @param ... Further arguments passed to [brms::make_stancode()]. See the
 #'   description of [brms::make_stancode()] for more details
 #'
 #' @returns A character string containing the fully commented Stan code to fit a
 #'   bmm model.
 #'
-#'
 #' @seealso [supported_models()], [brms::make_stancode()]
-#'
 #' @export
-#'
 #' @keywords extract_info
-#'
 #' @examples
 #' \dontrun{
 #' # generate artificial data from the Signal Discrimination Model
@@ -644,15 +635,29 @@ use_model_template <- function(model_name,
 #' ff <- bmmformula(c ~ 1,
 #'                  kappa ~ 1)
 #'
-#' # fit the model
+#' # generate the Stan code (if you are using brms version 2.20.14 or later)
+#' make_stancode(formula = ff,
+#'               data = dat,
+#'               model = sdmSimple(resp_err = "y"))
+#'
+#' # generate the Stan code (if you are using an older version of brms)
 #' get_stancode(formula = ff,
 #'              data = dat,
-#'              model = sdmSimple(resp_err = "y")
-#' )
+#'              model = sdmSimple(resp_err = "y"))
 #' }
 #'
 get_stancode <- function(formula, data, model, prior=NULL, ...) {
+  if (utils::packageVersion('brms') >= "2.20.14") {
+    message("get_stancode is deprecated. Please use make_stancode() instead.")
+    return(brms::make_stancode(formula = formula, data = data,
+                               model = model, prior = prior, ...))
+  }
+  make_stancode.bmmformula(formula = formula, data = data,
+                           model = model, prior = prior, ...)
+}
 
+#' @rdname get_stancode
+make_stancode.bmmformula <- function(formula, data, model, prior=NULL, ...) {
   # check model, formula and data, and transform data if necessary
   model <- check_model(model,data)
   data <- check_data(model, data, formula)
@@ -677,20 +682,7 @@ get_stancode <- function(formula, data, model, prior=NULL, ...) {
 #'   `bmm`. Given the `model`, the `data` and the `formula` for the model, this
 #'   function will return just the parameters block. Useful for figuring out
 #'   which paramters you can set initial values on
-#' @param formula An object of class `bmmformula`. A symbolic description of
-#'   the model to be fitted.
-#' @param data An object of class data.frame, containing data of all variables
-#'   used in the model. The names of the variables must match the variable names
-#'   passed to the `bmmmodel` object for required argurments.
-#' @param model A description of the model to be fitted. This is a call to a
-#'   `bmmmodel` such as `mixture3p()` function. Every model function has a
-#'   number of required arguments which need to be specified within the function
-#'   call. Call [supported_models()] to see the list of supported models and
-#'   their required arguments
-#' @param prior One or more `brmsprior` objects created by [brms::set_prior()]
-#'   or related functions and combined using the c method or the + operator. See
-#'   also [get_model_prior()] for more help. Not necessary for the default model
-#'   fitting, but you can provide prior constraints to model parameters
+#' @inheritParams fit_model
 #' @param ... Further arguments passed to [brms::make_stancode()]. See the
 #'   description of [brms::make_stancode()] for more details
 #'
@@ -703,7 +695,7 @@ get_stancode <- function(formula, data, model, prior=NULL, ...) {
 #' @seealso [supported_models()], [get_stancode()]
 #'
 #' @export
-get_stancode_parblock <- function(formula, data, model, prior=NULL, ...) {
+make_stancode_parblock <- function(formula, data, model, prior=NULL, ...) {
   stancode <- get_stancode(formula, data, model, prior, ...)
   .extract_parblock(stancode)
 }
diff --git a/R/helpers-prior.R b/R/helpers-prior.R
index be1049de..e4087ae3 100644
--- a/R/helpers-prior.R
+++ b/R/helpers-prior.R
@@ -1,34 +1,21 @@
-# internal function to combine two priors (e.g. the default prior with the user given prior)
-# parts present in prior2 will overwrite the corresponding parts in prior1
-combine_prior <- function(prior1, prior2) {
-  if (!is.null(prior2)) {
-    combined_prior <- dplyr::anti_join(prior1, prior2, by=c('class', 'dpar','nlpar','coef','group','resp'))
-    prior <- combined_prior + prior2
-  } else {
-    prior <- prior1
-  }
-  return(prior)
-}
-
-
-#' @title Get Default priors for Measurement Models specified in BRMS
-#' @description Obtain the default priors for a Bayesian multilevel measurement model,
-#'   as well as information for which parameters priors can be specified.
-#'   Given the `model`, the `data` and the `formula` for the model, this function will return
-#'   the default priors that would be used to estimate the model. Additionally, it will
-#'   return all model parameters that have no prior specified (flat priors). This can help to
-#'   get an idea about which priors need to be specified and also know which priors were
-#'   used if no user-specified priors were passed to the [fit_model()] function.
-#' @param formula An object of class `bmmformula`. A symbolic description of
-#'   the model to be fitted.
-#' @param data An object of class data.frame, containing data of all variables
-#'   used in the model. The names of the variables must match the variable names
-#'   passed to the `bmmmodel` object for required argurments.
-#' @param model A description of the model to be fitted. This is a call to a
-#'   `bmmmodel` such as `mixture3p()` function. Every model function has a
-#'   number of required arguments which need to be specified within the function
-#'   call. Call [supported_models()] to see the list of supported models and
-#'   their required arguments
+#' @title Get Default priors for Measurement Models specified in BMM
+#' @description Obtain the default priors for a Bayesian multilevel measurement
+#'   model, as well as information for which parameters priors can be specified.
+#'   Given the `model`, the `data` and the `formula` for the model, this
+#'   function will return the default priors that would be used to estimate the
+#'   model. Additionally, it will return all model parameters that have no prior
+#'   specified (flat priors). This can help to get an idea about which priors
+#'   need to be specified and also know which priors were used if no
+#'   user-specified priors were passed to the [fit_model()] function.
+#'
+#'   If you are using *brms* version 2.20.14 or later, you should use
+#'   [get_prior][brms::get_prior()] directly with the `bmmformula` object. If you are using an
+#'   older version of *brms*, you have to use [get_model_prior()] to obtain the
+#'   default priors. The usage of [get_model_prior()] is deprecated and will be
+#'   removed in future versions of *bmm*.
+#'
+#'
+#' @inheritParams fit_model
 #' @param ... Further arguments passed to [brms::get_prior()]. See the
 #'   description of [brms::get_prior()] for more details
 #'
@@ -36,10 +23,12 @@ combine_prior <- function(prior1, prior2) {
 #'
 #'   Type `help(package=bmm)` for a full list of available help topics.
 #'
-#' @returns A data.frame with columns specifying the `prior`, the `class`, the `coef` and `group`
-#'    for each of the priors specified. Separate rows contain the information on the
-#'    parameters (or parameter classes) for which priors can be specified.
+#' @returns A data.frame with columns specifying the `prior`, the `class`, the
+#'   `coef` and `group` for each of the priors specified. Separate rows contain
+#'   the information on the parameters (or parameter classes) for which priors
+#'   can be specified.
 #'
+#' @name get_model_prior
 #'
 #' @seealso [supported_models()], [brms::get_prior()]
 #'
@@ -57,14 +46,32 @@ combine_prior <- function(prior1, prior2) {
 #'           c ~ 1,
 #'           kappa ~ 1)
 #'
-#' # fit the model
-#' get_model_prior(formula = ff,
-#'                 data = dat,
-#'                 model = sdmSimple()
-#' )
-#' }
 #'
+#' if (utils::packageVersion('brms') >= "2.20.14") {
+#'   # extract the default bmm prior (if using brms version 2.20.14 or later)
+#'   get_prior(formula = ff,
+#'             data = dat,
+#'             model = sdmSimple())
+#' } else {
+#'    # (if using an older version of brms)
+#'    get_model_prior(formula = ff,
+#'                    data = dat,
+#'                    model = sdmSimple())
+#' }
+#' }
+#' @export
 get_model_prior <- function(formula, data, model, ...) {
+  if (utils::packageVersion('brms') >= "2.20.14") {
+    message("get_model_prior is deprecated. Please use get_prior() instead.")
+    return(brms::get_prior(formula = formula, data = data, model = model, ...))
+  }
+  get_prior.bmmformula(formula = formula, data = data, model = model, ...)
+}
+
+
+
+#' @rdname get_model_prior
+get_prior.bmmformula <- function(formula, data, model, ...) {
   model <- check_model(model, data)
   data <- check_data(model, data, formula)
   formula <- check_formula(model, data, formula)
@@ -77,7 +84,6 @@ get_model_prior <- function(formula, data, model, ...) {
   combine_prior(brms_priors, prior_args$prior)
 }
 
-
 #' @title construct constant priors to fix fixed model parameters
 #' @param model a `bmmmodel` object
 #' @param additional_pars a list of name=value pairs to fix additional
@@ -233,3 +239,16 @@ set_default_prior <- function(bmmformula, data, prior_list) {
   }
   prior
 }
+
+
+# internal function to combine two priors (e.g. the default prior with the user given prior)
+# parts present in prior2 will overwrite the corresponding parts in prior1
+combine_prior <- function(prior1, prior2) {
+  if (!is.null(prior2)) {
+    combined_prior <- dplyr::anti_join(prior1, prior2, by=c('class', 'dpar','nlpar','coef','group','resp'))
+    prior <- combined_prior + prior2
+  } else {
+    prior <- prior1
+  }
+  return(prior)
+}
diff --git a/R/zzz.R b/R/zzz.R
index 85c1e097..40eb1100 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -1,5 +1,11 @@
 .onLoad <- function(libname, pkgname) {
   suppressMessages(bmm_options(reset_options = TRUE))
+
+  if (utils::packageVersion('brms') >= "2.20.14") {
+    #' @exportS3Method brms::get_prior bmmformula
+    #' @exportS3Method brms::make_standata bmmformula
+    #' @exportS3Method brms::make_stancode bmmformula
+  }
 }
 
 .onAttach <- function(libname, pkgname) {
diff --git a/man/bmm-package.Rd b/man/bmm-package.Rd
index f95c1da2..626e463f 100644
--- a/man/bmm-package.Rd
+++ b/man/bmm-package.Rd
@@ -27,7 +27,7 @@ Authors:
 
 Other contributors:
 \itemize{
-  \item Paul B<U+00FC>rkner \email{paul.buerkner@gmail.com} (Creator of brms, a package for Bayesian regression model that this package builds upon.) [copyright holder]
+  \item Paul Bürkner \email{paul.buerkner@gmail.com} (Creator of brms, a package for Bayesian regression model that this package builds upon.) [copyright holder]
 }
 
 }
diff --git a/man/get_model_prior.Rd b/man/get_model_prior.Rd
index 387739c5..129cab19 100644
--- a/man/get_model_prior.Rd
+++ b/man/get_model_prior.Rd
@@ -2,13 +2,16 @@
 % Please edit documentation in R/helpers-prior.R
 \name{get_model_prior}
 \alias{get_model_prior}
-\title{Get Default priors for Measurement Models specified in BRMS}
+\alias{get_prior.bmmformula}
+\title{Get Default priors for Measurement Models specified in BMM}
 \usage{
 get_model_prior(formula, data, model, ...)
+
+\method{get_prior}{bmmformula}(formula, data, model, ...)
 }
 \arguments{
-\item{formula}{An object of class \code{bmmformula}. A symbolic description of
-the model to be fitted.}
+\item{formula}{An object of class \code{bmmformula}. A symbolic description of the
+model to be fitted.}
 
 \item{data}{An object of class data.frame, containing data of all variables
 used in the model. The names of the variables must match the variable names
@@ -24,18 +27,26 @@ their required arguments}
 description of \code{\link[brms:get_prior]{brms::get_prior()}} for more details}
 }
 \value{
-A data.frame with columns specifying the \code{prior}, the \code{class}, the \code{coef} and \code{group}
-for each of the priors specified. Separate rows contain the information on the
-parameters (or parameter classes) for which priors can be specified.
+A data.frame with columns specifying the \code{prior}, the \code{class}, the
+\code{coef} and \code{group} for each of the priors specified. Separate rows contain
+the information on the parameters (or parameter classes) for which priors
+can be specified.
 }
 \description{
-Obtain the default priors for a Bayesian multilevel measurement model,
-as well as information for which parameters priors can be specified.
-Given the \code{model}, the \code{data} and the \code{formula} for the model, this function will return
-the default priors that would be used to estimate the model. Additionally, it will
-return all model parameters that have no prior specified (flat priors). This can help to
-get an idea about which priors need to be specified and also know which priors were
-used if no user-specified priors were passed to the \code{\link[=fit_model]{fit_model()}} function.
+Obtain the default priors for a Bayesian multilevel measurement
+model, as well as information for which parameters priors can be specified.
+Given the \code{model}, the \code{data} and the \code{formula} for the model, this
+function will return the default priors that would be used to estimate the
+model. Additionally, it will return all model parameters that have no prior
+specified (flat priors). This can help to get an idea about which priors
+need to be specified and also know which priors were used if no
+user-specified priors were passed to the \code{\link[=fit_model]{fit_model()}} function.
+
+If you are using \emph{brms} version 2.20.14 or later, you should use
+\link[brms:get_prior]{get_prior} directly with the \code{bmmformula} object. If you are using an
+older version of \emph{brms}, you have to use \code{\link[=get_model_prior]{get_model_prior()}} to obtain the
+default priors. The usage of \code{\link[=get_model_prior]{get_model_prior()}} is deprecated and will be
+removed in future versions of \emph{bmm}.
 }
 \details{
 The following models are supported:
@@ -62,13 +73,19 @@ ff <- bmf(y ~ 1,
           c ~ 1,
           kappa ~ 1)
 
-# fit the model
-get_model_prior(formula = ff,
-                data = dat,
-                model = sdmSimple()
-)
-}
 
+if (utils::packageVersion('brms') >= "2.20.14") {
+  # extract the default bmm prior (if using brms version 2.20.14 or later)
+  get_prior(formula = ff,
+            data = dat,
+            model = sdmSimple())
+} else {
+   # (if using an older version of brms)
+   get_model_prior(formula = ff,
+                   data = dat,
+                   model = sdmSimple())
+}
+}
 }
 \seealso{
 \code{\link[=supported_models]{supported_models()}}, \code{\link[brms:get_prior]{brms::get_prior()}}
diff --git a/man/get_stancode.Rd b/man/get_stancode.Rd
index 3253f6cb..f7220f2a 100644
--- a/man/get_stancode.Rd
+++ b/man/get_stancode.Rd
@@ -2,13 +2,16 @@
 % Please edit documentation in R/helpers-model.R
 \name{get_stancode}
 \alias{get_stancode}
+\alias{make_stancode.bmmformula}
 \title{Generate Stan code for bmm models}
 \usage{
 get_stancode(formula, data, model, prior = NULL, ...)
+
+\method{make_stancode}{bmmformula}(formula, data, model, prior = NULL, ...)
 }
 \arguments{
-\item{formula}{An object of class \code{bmmformula}. A symbolic description of
-the model to be fitted.}
+\item{formula}{An object of class \code{bmmformula}. A symbolic description of the
+model to be fitted.}
 
 \item{data}{An object of class data.frame, containing data of all variables
 used in the model. The names of the variables must match the variable names
@@ -33,9 +36,16 @@ A character string containing the fully commented Stan code to fit a
 bmm model.
 }
 \description{
-A wrapper around \code{brms::make_stancode()} for models specified with
-\code{bmm}. Given the \code{model}, the \code{data} and the \code{formula} for the model, this
-function will return the combined stan code generated by \code{bmm} and \code{brms}
+A wrapper around \code{brms::make_stancode()} for models specified
+with \code{bmm}. Given the \code{model}, the \code{data} and the \code{formula} for the model,
+this function will return the combined stan code generated by \code{bmm} and
+\code{brms}
+
+If you are using \emph{brms} version 2.20.14 or later, you should use
+\code{\link[=make_stancode]{make_stancode()}} directly with the \code{bmmformula} object. If you are using
+an older version of \emph{brms}, you have to use \code{\link[=get_stancode]{get_stancode()}} to obtain the
+default priors. The usage of \code{\link[=get_stancode]{get_stancode()}} is deprecated and will be
+removed in future versions of \emph{bmm}.
 }
 \examples{
 \dontrun{
@@ -46,11 +56,15 @@ dat <- data.frame(y=rsdm(n=2000))
 ff <- bmmformula(c ~ 1,
                  kappa ~ 1)
 
-# fit the model
+# generate the Stan code (if you are using brms version 2.20.14 or later)
+make_stancode(formula = ff,
+              data = dat,
+              model = sdmSimple(resp_err = "y"))
+
+# generate the Stan code (if you are using an older version of brms)
 get_stancode(formula = ff,
              data = dat,
-             model = sdmSimple(resp_err = "y")
-)
+             model = sdmSimple(resp_err = "y"))
 }
 
 }
diff --git a/man/get_standata.Rd b/man/get_standata.Rd
index 16218944..b9fa38bf 100644
--- a/man/get_standata.Rd
+++ b/man/get_standata.Rd
@@ -2,13 +2,16 @@
 % Please edit documentation in R/helpers-data.R
 \name{get_standata}
 \alias{get_standata}
+\alias{make_standata.bmmformula}
 \title{Generate data for \code{bmm} models to be passed to Stan}
 \usage{
 get_standata(formula, data, model, prior = NULL, ...)
+
+\method{make_standata}{bmmformula}(formula, data, model, prior = NULL, ...)
 }
 \arguments{
-\item{formula}{An object of class \code{brmsformula}. A symbolic description of
-the model to be fitted.}
+\item{formula}{An object of class \code{bmmformula}. A symbolic description of the
+model to be fitted.}
 
 \item{data}{An object of class data.frame, containing data of all variables
 used in the model. The names of the variables must match the variable names
@@ -37,6 +40,12 @@ A wrapper around \code{brms::make_standata()} for models specified
 with \code{bmm}. Given the \code{model}, the \code{data} and the \code{formula} for the model,
 this function will return the combined stan data generated by \code{bmm} and
 \code{brms}
+
+If you are using \emph{brms} version 2.20.14 or later, you can use
+\code{\link[=make_standata]{make_standata()}} directly with the \code{bmmformula} object. If you are using
+an older version of \emph{brms}, you have to use \code{\link[=get_standata]{get_standata()}} to obtain the
+default priors. The usage of \code{\link[=get_standata]{get_standata()}} is deprecated and will be
+removed in future versions of \emph{bmm}.
 }
 \examples{
 \dontrun{
@@ -47,11 +56,18 @@ dat <- data.frame(y=rsdm(n=2000))
 ff <- bmf(c ~ 1,
           kappa ~ 1)
 
-# fit the model
-get_standata(formula = ff,
-             data = dat,
-             model = sdmSimple(resp_err = "y")
-)
+
+if (utils::packageVersion('brms') >= "2.20.14") {
+  # generate the stan data (if using brms version 2.20.14 or later)
+  make_standata(formula = ff,
+                data = dat,
+                model = sdmSimple(resp_err = "y"))
+} else {
+  # generate the stan data (if using an older version of brms)
+  get_standata(formula = ff,
+               data = dat,
+               model = sdmSimple(resp_err = "y"))
+}
 }
 
 }
diff --git a/man/get_stancode_parblock.Rd b/man/make_stancode_parblock.Rd
similarity index 92%
rename from man/get_stancode_parblock.Rd
rename to man/make_stancode_parblock.Rd
index 59c12d72..b38ebadd 100644
--- a/man/get_stancode_parblock.Rd
+++ b/man/make_stancode_parblock.Rd
@@ -1,14 +1,14 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/helpers-model.R
-\name{get_stancode_parblock}
-\alias{get_stancode_parblock}
+\name{make_stancode_parblock}
+\alias{make_stancode_parblock}
 \title{Get the parameter block from a generated Stan code for bmm models}
 \usage{
-get_stancode_parblock(formula, data, model, prior = NULL, ...)
+make_stancode_parblock(formula, data, model, prior = NULL, ...)
 }
 \arguments{
-\item{formula}{An object of class \code{bmmformula}. A symbolic description of
-the model to be fitted.}
+\item{formula}{An object of class \code{bmmformula}. A symbolic description of the
+model to be fitted.}
 
 \item{data}{An object of class data.frame, containing data of all variables
 used in the model. The names of the variables must match the variable names
diff --git a/tests/testthat/test-helpers-data.R b/tests/testthat/test-helpers-data.R
index 070489b9..60352b03 100644
--- a/tests/testthat/test-helpers-data.R
+++ b/tests/testthat/test-helpers-data.R
@@ -195,6 +195,37 @@ test_that("rad2deg returns the correct values for 0, pi/2, 2*pi", {
   expect_equal(wrap(rad2deg(x), radians = F), rad2deg(wrap(x)))
 })
 
+test_that("make_standata() works with brmsformula", {
+  ff <- brms::bf(count ~ zAge + zBase * Trt + (1|patient))
+  sd <- make_standata(ff, data = brms::epilepsy, family = poisson())
+  expect_equal(class(sd)[1], "standata")
+})
+
+test_that("make_standata() works with formula", {
+  ff <- count ~ zAge + zBase * Trt + (1|patient)
+  sd <- make_standata(ff, data = brms::epilepsy, family = poisson())
+  expect_equal(class(sd)[1], "standata")
+})
+
+test_that("make_standata() works with bmmformula if brms >= 2.20.14", {
+  # define formula
+  ff <- bmmformula(kappa ~ 1,
+                   thetat ~ 1,
+                   thetant ~ 1)
+
+  # simulate data
+  dat <- OberauerLin_2017
+
+  # fit the model
+  if (utils::packageVersion("brms") >= "2.20.14") {
+    sd <- make_standata(formula = ff,
+                           data = dat,
+                           model = mixture3p(resp_err = "dev_rad",
+                                         nt_features = 'col_nt',
+                                         setsize = "set_size", regex = T))
+    expect_equal(class(sd)[1], "standata")
+  }
+})
 
 test_that("get_standata() returns a standata class", {
   ff <- bmmformula(kappa ~ 1,
diff --git a/tests/testthat/test-helpers-model.R b/tests/testthat/test-helpers-model.R
index a4ee35bf..992938bb 100644
--- a/tests/testthat/test-helpers-model.R
+++ b/tests/testthat/test-helpers-model.R
@@ -97,3 +97,35 @@ test_that("get_stancode() returns a string", {
                            model = mixture3p(resp_err = "y", nt_features = paste0('nt',1,'_loc'), setsize = 2))
   expect_equal(class(stancode)[1], "character")
 })
+
+test_that("make_stancode() works with brmsformula", {
+  ff <- brms::bf(count ~ zAge + zBase * Trt + (1|patient))
+  sd <- make_stancode(ff, data = brms::epilepsy, family = poisson())
+  expect_equal(class(sd)[1], "character")
+})
+
+test_that("make_stancode() works with formula", {
+  ff <- count ~ zAge + zBase * Trt + (1|patient)
+  sd <- make_stancode(ff, data = brms::epilepsy, family = poisson())
+  expect_equal(class(sd)[1], "character")
+})
+
+test_that("make_stancode() works with bmmformula if brms >= 2.20.14", {
+  # define formula
+  ff <- bmmformula(kappa ~ 1,
+                   thetat ~ 1,
+                   thetant ~ 1)
+
+  # simulate data
+  dat <- OberauerLin_2017
+
+  # fit the model
+  if (utils::packageVersion("brms") >= "2.20.14") {
+    sd <- make_stancode(formula = ff,
+                        data = dat,
+                        model = mixture3p(resp_err = "dev_rad",
+                                          nt_features = 'col_nt',
+                                          setsize = "set_size", regex = T))
+    expect_equal(class(sd)[1], "character")
+  }
+})
diff --git a/tests/testthat/test-helpers-prior.R b/tests/testthat/test-helpers-prior.R
index 4fd4eeb6..9ea98584 100644
--- a/tests/testthat/test-helpers-prior.R
+++ b/tests/testthat/test-helpers-prior.R
@@ -1,19 +1,33 @@
-test_that("get_model_prior() returns a brmsprior object", {
+test_that("get_prior() works with brmsformula", {
+  ff <- brms::bf(count ~ zAge + zBase * Trt + (1|patient))
+  prior <- get_prior(ff, data = brms::epilepsy, family = poisson())
+  expect_equal(class(prior)[1], "brmsprior")
+})
+
+test_that("get_prior() works with formula", {
+  ff <- count ~ zAge + zBase * Trt + (1|patient)
+  prior <- get_prior(ff, data = brms::epilepsy, family = poisson())
+  expect_equal(class(prior)[1], "brmsprior")
+})
+
+test_that("get_prior() works with bmmformula if brms >= 2.20.14", {
   # define formula
   ff <- bmmformula(kappa ~ 1,
-                    thetat ~ 1,
-                    thetant ~ 1)
+                   thetat ~ 1,
+                   thetant ~ 1)
 
   # simulate data
-  dat <- data.frame(y = rmixture3p(n = 200),
-                    nt1_loc = 2,
-                    nt2_loc = -1.5)
+  dat <- OberauerLin_2017
 
   # fit the model
-  prior <- get_model_prior(formula = ff,
-                           data = dat,
-                           model = mixture3p(resp_err = "y", nt_features = paste0('nt',1,'_loc'), setsize = 2))
-  expect_equal(class(prior)[1], "brmsprior")
+  if (utils::packageVersion("brms") >= "2.20.14") {
+    prior <- get_prior(formula = ff,
+                       data = dat,
+                       model = mixture3p(resp_err = "dev_rad",
+                                         nt_features = 'col_nt',
+                                         setsize = "set_size", regex = T))
+    expect_equal(class(prior)[1], "brmsprior")
+  }
 })
 
 test_that("combine prior returns a brmsprior object", {