diff --git a/NAMESPACE b/NAMESPACE
index 874649f..64d2dad 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,6 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 S3method(as_draws,measrfit)
+S3method(as_measrfit,default)
 S3method(c,measrprior)
 S3method(fit_m2,measrdcm)
 S3method(loo,measrfit)
@@ -21,6 +22,7 @@ export(add_reliability)
 export(add_respondent_estimates)
 export(as_draws)
 export(as_label)
+export(as_measrfit)
 export(as_name)
 export(create_profiles)
 export(default_dcm_priors)
@@ -35,6 +37,7 @@ export(loo_compare)
 export(measr_dcm)
 export(measr_examples)
 export(measr_extract)
+export(measrfit)
 export(measrprior)
 export(prior)
 export(prior_)
diff --git a/NEWS.md b/NEWS.md
index 126f766..8bfaa76 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,6 +2,8 @@
 
 * Updated reliability functionality to allow for the calculation of accuracy and consistency with different thresholds for determining attribute classifications.
 
+* Added new `measrfit()` function for creating measrfit objects from *Stan* models that were not originally created with measr.
+
 # measr 1.0.0
 
 ## New documentation
diff --git a/R/measrfit-class.R b/R/measrfit-class.R
index adf656c..e92c64c 100644
--- a/R/measrfit-class.R
+++ b/R/measrfit-class.R
@@ -1,3 +1,134 @@
+#' Create a `measrfit` object
+#'
+#' Models fitted with **measr** are represented as a `measrfit` object. If a
+#' model is estimated with *Stan*, but not **measr**, a `measrfit` object can be
+#' created in order to access other functionality in **measr** (e.g., model fit,
+#' reliability).
+#'
+#' @param data The data and Q-matrix used to estimate the model.
+#' @param type The type of DCM that was estimated.
+#' @param prior A [measrprior][measrprior()] object containing information on
+#'   the priors used in the model.
+#' @param stancode The model code in **Stan** language.
+#' @param method The method used to fit the model.
+#' @param algorithm The name of the algorithm used to fit the model.
+#' @param backend The name of the backend used to fit the model.
+#' @param model The fitted Stan model. This will object of class
+#'   [rstan::stanfit-class] if `backend = "rstan"` and
+#'   [`CmdStanMCMC`](https://mc-stan.org/cmdstanr/reference/CmdStanMCMC.html)
+#'   if `backend = "cmdstanr"` was specified when fitting the model.
+#' @param respondent_estimates An empty list for adding estimated person
+#'   parameters after fitting the model.
+#' @param fit An empty list for adding model fit information after fitting the
+#'   model.
+#' @param criteria An empty list for adding information criteria after fitting
+#'   the model.
+#' @param reliability An empty list for adding reliability information after
+#'   fitting the model.
+#' @param file Optional name of a file which the model objects was saved to
+#'   or loaded from.
+#' @param version The versions of **measr**, **Stan**, **rstan** and/or
+#'   **cmdstanr** that were used to fit the model.
+#' @param class Additional classes to be added (e.g., `measrdcm` for a
+#'   diagnostic classification model).
+#'
+#' @return A [measrfit][measrfit-class] object.
+#' @export
+#' @seealso [measrfit-class], [measr_dcm()]
+#' @examplesIf measr_examples()
+#' rstn_mdm_lcdm <- measr_dcm(
+#'   data = mdm_data, missing = NA, qmatrix = mdm_qmatrix,
+#'   resp_id = "respondent", item_id = "item", type = "lcdm",
+#'   method = "optim", seed = 63277, backend = "rstan"
+#' )
+#'
+#' new_obj <- measrfit(
+#'   data = rstn_mdm_lcdm$data,
+#'   type = rstn_mdm_lcdm$type,
+#'   prior = rstn_mdm_lcdm$prior,
+#'   stancode = rstn_mdm_lcdm$stancode,
+#'   method = rstn_mdm_lcdm$method,
+#'   algorithm = rstn_mdm_lcdm$algorithm,
+#'   backend = rstn_mdm_lcdm$backend,
+#'   model = rstn_mdm_lcdm$model,
+#'   respondent_estimates = rstn_mdm_lcdm$respondent_estimates,
+#'   fit = rstn_mdm_lcdm$fit,
+#'   criteria = rstn_mdm_lcdm$criteria,
+#'   reliability = rstn_mdm_lcdm$reliability,
+#'   file = rstn_mdm_lcdm$file,
+#'   version = rstn_mdm_lcdm$version,
+#'   class = "measrdcm"
+#' )
+measrfit <- function(data = list(), type = character(),
+                     prior = default_dcm_priors(type = type),
+                     stancode = character(), method = character(),
+                     algorithm = character(), backend = character(),
+                     model = NULL, respondent_estimates = list(),
+                     fit = list(), criteria = list(), reliability = list(),
+                     file = NULL, version = list(), class = character()) {
+  obj <- list(data = data,
+              type = type,
+              prior = prior,
+              stancode = stancode,
+              method = method,
+              algorithm = algorithm,
+              backend = backend,
+              model = model,
+              respondent_estimates = respondent_estimates,
+              fit = fit,
+              criteria = criteria,
+              reliability = reliability,
+              file = file,
+              version = version)
+
+  validate_measrfit(new_measrfit(obj, class = class))
+}
+
+#' Coerce objects to a `measrfit`
+#'
+#' @param x An object to be coerced to a `measrfit`.
+#' @param class Additional classes to be added (e.g., `measrdcm` for a
+#'   diagnostic classification model).
+#'
+#' @return An object of class [measrfit-class].
+#' @export
+#' @seealso [measrfit-class], [measrfit()]
+#'
+#' @examplesIf measr_examples()
+#' rstn_mdm_lcdm <- measr_dcm(
+#'   data = mdm_data, missing = NA, qmatrix = mdm_qmatrix,
+#'   resp_id = "respondent", item_id = "item", type = "lcdm",
+#'   method = "optim", seed = 63277, backend = "rstan"
+#' )
+#'
+#' new_obj <- as_measrfit(rstn_mdm_lcdm, class = "measrdcm")
+as_measrfit <- function(x, class = character()) {
+  UseMethod("as_measrfit")
+}
+
+#' @export
+#' @rdname as_measrfit
+as_measrfit.default <- function(x, class = character()) {
+  measrfit(
+    data = x$data,
+    type = x$type,
+    prior = x$prior,
+    stancode = x$stancode,
+    method = x$method,
+    algorithm = x$algorithm,
+    backend = x$backend,
+    model = x$model,
+    respondent_estimates = x$respondent_estimates,
+    fit = x$fit,
+    criteria = x$criteria,
+    reliability = x$reliability,
+    file = x$file,
+    version = x$version,
+    class = class
+  )
+}
+
+
 #' Class `measrfit` of models fitted with the **measr** package
 #'
 #' Models fitted with the **measr** package are represented as a `measrfit`
@@ -5,7 +136,6 @@
 #' relevant information.
 #'
 #' @name measrfit-class
-#' @aliases measrfit
 #' @docType class
 #'
 #' @slot data The data and Q-matrix used to estimate the model.
@@ -46,3 +176,51 @@ new_measrfit <- function(model = list(), ..., class = character()) {
 new_measrdcm <- function(x) {
   new_measrfit(x, class = "measrdcm")
 }
+
+validate_measrfit <- function(x) {
+  # check names ----------------------------------------------------------------
+  stopifnot(all(names(x) == c("data", "type", "prior", "stancode", "method",
+                              "algorithm", "backend", "model",
+                              "respondent_estimates", "fit", "criteria",
+                              "reliability", "file", "version")))
+
+  # check types ----------------------------------------------------------------
+  stopifnot(is.list(x$data))
+  stopifnot(tibble::is_tibble(x$data$data))
+  stopifnot(all(colnames(x$data$data) == c("resp_id", "item_id", "score")))
+  stopifnot(tibble::is_tibble(x$data$qmatrix))
+  stopifnot(is.character(x$data$resp_id))
+  stopifnot(is.character(x$data$item_id))
+  stopifnot(is.character(x$type))
+  stopifnot(x$type %in% dcm_choices())
+  stopifnot(is.measrprior(x$prior))
+  stopifnot(is.character(x$stancode))
+  stopifnot(is.character(x$method))
+  stopifnot(x$method %in% c("mcmc", "optim"))
+  stopifnot(is.character(x$algorithm))
+  stopifnot(is.character(x$backend))
+  stopifnot(x$backend %in% backend_choices())
+  if (x$backend == "rstan" && x$method == "optim") {
+    stopifnot(is.list(x$model))
+  } else if (x$backend == "rstan" && x$method == "mcmc") {
+    stopifnot(any(class(x$model) == "stanfit"))
+  } else if (x$backend == "cmdstanr") {
+    stopifnot(any(class(x$model) == "CmdStanFit"))
+  }
+  stopifnot(is.list(x$respondent_estimates))
+  stopifnot(is.list(x$fit))
+  stopifnot(is.list(x$criteria))
+  stopifnot(is.list(x$reliability))
+  stopifnot(is.null(x$file) || is.character(x$file))
+  stopifnot(is.list(x$version))
+  stopifnot(is.package_version(x$version$R))
+  stopifnot(is.package_version(x$version[[2]]))
+  stopifnot(is.package_version(x$version$rstan))
+  stopifnot(is.package_version(x$version$StanHeaders))
+  if (x$backend == "cmdstanr") {
+    stopifnot(is.package_version(x$version$cmdstanr))
+    stopifnot(is.package_version(x$version$cmdstan))
+  }
+
+  x
+}
diff --git a/man/as_measrfit.Rd b/man/as_measrfit.Rd
new file mode 100644
index 0000000..2b02c83
--- /dev/null
+++ b/man/as_measrfit.Rd
@@ -0,0 +1,37 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/measrfit-class.R
+\name{as_measrfit}
+\alias{as_measrfit}
+\alias{as_measrfit.default}
+\title{Coerce objects to a \code{measrfit}}
+\usage{
+as_measrfit(x, class = character())
+
+\method{as_measrfit}{default}(x, class = character())
+}
+\arguments{
+\item{x}{An object to be coerced to a \code{measrfit}.}
+
+\item{class}{Additional classes to be added (e.g., \code{measrdcm} for a
+diagnostic classification model).}
+}
+\value{
+An object of class \linkS4class{measrfit}.
+}
+\description{
+Coerce objects to a \code{measrfit}
+}
+\examples{
+\dontshow{if (measr_examples()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+rstn_mdm_lcdm <- measr_dcm(
+  data = mdm_data, missing = NA, qmatrix = mdm_qmatrix,
+  resp_id = "respondent", item_id = "item", type = "lcdm",
+  method = "optim", seed = 63277, backend = "rstan"
+)
+
+new_obj <- as_measrfit(rstn_mdm_lcdm, class = "measrdcm")
+\dontshow{\}) # examplesIf}
+}
+\seealso{
+\linkS4class{measrfit}, \code{\link[=measrfit]{measrfit()}}
+}
diff --git a/man/loo.measrfit.Rd b/man/loo.measrfit.Rd
index f1c4204..c6f473c 100644
--- a/man/loo.measrfit.Rd
+++ b/man/loo.measrfit.Rd
@@ -14,13 +14,14 @@
 \item{r_eff}{Vector of relative effective sample size estimates for the
 likelihood (\code{exp(log_lik)}) of each observation. This is related to
 the relative efficiency of estimating the normalizing term in
-self-normalizing importance sampling when using posterior draws obtained
+self-normalized importance sampling when using posterior draws obtained
 with MCMC. If MCMC draws are used and \code{r_eff} is not provided then
 the reported PSIS effective sample sizes and Monte Carlo error estimates
-will be over-optimistic. If the posterior draws are independent then
-\code{r_eff=1} and can be omitted. The warning message thrown when \code{r_eff} is
-not specified can be disabled by setting \code{r_eff} to \code{NA}. See the
-\code{\link[loo:relative_eff]{relative_eff()}} helper functions for computing \code{r_eff}.}
+can be over-optimistic. If the posterior draws are (near) independent then
+\code{r_eff=1} can be used. \code{r_eff} has to be a scalar (same value is used
+for all observations) or a vector with length equal to the number of
+observations. The default value is 1. See the \code{\link[loo:relative_eff]{relative_eff()}} helper
+functions for help computing \code{r_eff}.}
 
 \item{force}{If the LOO criterion has already been added to the model object
 with \code{\link[=add_criterion]{add_criterion()}}, should it be recalculated. Default is \code{FALSE}.}
diff --git a/man/measrfit-class.Rd b/man/measrfit-class.Rd
index cad99b9..c6ed252 100644
--- a/man/measrfit-class.Rd
+++ b/man/measrfit-class.Rd
@@ -3,7 +3,6 @@
 \docType{class}
 \name{measrfit-class}
 \alias{measrfit-class}
-\alias{measrfit}
 \title{Class \code{measrfit} of models fitted with the \strong{measr} package}
 \description{
 Models fitted with the \strong{measr} package are represented as a \code{measrfit}
diff --git a/man/measrfit.Rd b/man/measrfit.Rd
new file mode 100644
index 0000000..43913f7
--- /dev/null
+++ b/man/measrfit.Rd
@@ -0,0 +1,105 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/measrfit-class.R
+\name{measrfit}
+\alias{measrfit}
+\title{Create a \code{measrfit} object}
+\usage{
+measrfit(
+  data = list(),
+  type = character(),
+  prior = default_dcm_priors(type = type),
+  stancode = character(),
+  method = character(),
+  algorithm = character(),
+  backend = character(),
+  model = NULL,
+  respondent_estimates = list(),
+  fit = list(),
+  criteria = list(),
+  reliability = list(),
+  file = NULL,
+  version = list(),
+  class = character()
+)
+}
+\arguments{
+\item{data}{The data and Q-matrix used to estimate the model.}
+
+\item{type}{The type of DCM that was estimated.}
+
+\item{prior}{A \link[=measrprior]{measrprior} object containing information on
+the priors used in the model.}
+
+\item{stancode}{The model code in \strong{Stan} language.}
+
+\item{method}{The method used to fit the model.}
+
+\item{algorithm}{The name of the algorithm used to fit the model.}
+
+\item{backend}{The name of the backend used to fit the model.}
+
+\item{model}{The fitted Stan model. This will object of class
+\link[rstan:stanfit-class]{rstan::stanfit} if \code{backend = "rstan"} and
+\href{https://mc-stan.org/cmdstanr/reference/CmdStanMCMC.html}{\code{CmdStanMCMC}}
+if \code{backend = "cmdstanr"} was specified when fitting the model.}
+
+\item{respondent_estimates}{An empty list for adding estimated person
+parameters after fitting the model.}
+
+\item{fit}{An empty list for adding model fit information after fitting the
+model.}
+
+\item{criteria}{An empty list for adding information criteria after fitting
+the model.}
+
+\item{reliability}{An empty list for adding reliability information after
+fitting the model.}
+
+\item{file}{Optional name of a file which the model objects was saved to
+or loaded from.}
+
+\item{version}{The versions of \strong{measr}, \strong{Stan}, \strong{rstan} and/or
+\strong{cmdstanr} that were used to fit the model.}
+
+\item{class}{Additional classes to be added (e.g., \code{measrdcm} for a
+diagnostic classification model).}
+}
+\value{
+A \link[=measrfit-class]{measrfit} object.
+}
+\description{
+Models fitted with \strong{measr} are represented as a \code{measrfit} object. If a
+model is estimated with \emph{Stan}, but not \strong{measr}, a \code{measrfit} object can be
+created in order to access other functionality in \strong{measr} (e.g., model fit,
+reliability).
+}
+\examples{
+\dontshow{if (measr_examples()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+rstn_mdm_lcdm <- measr_dcm(
+  data = mdm_data, missing = NA, qmatrix = mdm_qmatrix,
+  resp_id = "respondent", item_id = "item", type = "lcdm",
+  method = "optim", seed = 63277, backend = "rstan"
+)
+
+new_obj <- measrfit(
+  data = rstn_mdm_lcdm$data,
+  type = rstn_mdm_lcdm$type,
+  prior = rstn_mdm_lcdm$prior,
+  stancode = rstn_mdm_lcdm$stancode,
+  method = rstn_mdm_lcdm$method,
+  algorithm = rstn_mdm_lcdm$algorithm,
+  backend = rstn_mdm_lcdm$backend,
+  model = rstn_mdm_lcdm$model,
+  respondent_estimates = rstn_mdm_lcdm$respondent_estimates,
+  fit = rstn_mdm_lcdm$fit,
+  criteria = rstn_mdm_lcdm$criteria,
+  reliability = rstn_mdm_lcdm$reliability,
+  file = rstn_mdm_lcdm$file,
+  version = rstn_mdm_lcdm$version,
+  class = "measrdcm"
+)
+\dontshow{\}) # examplesIf}
+}
+\seealso{
+\linkS4class{measrfit}, \code{\link[=measr_dcm]{measr_dcm()}}
+}
diff --git a/man/model_evaluation.Rd b/man/model_evaluation.Rd
index 79641e2..2aa1146 100644
--- a/man/model_evaluation.Rd
+++ b/man/model_evaluation.Rd
@@ -56,13 +56,14 @@ file will not be updated.}
 \item{r_eff}{Vector of relative effective sample size estimates for the
 likelihood (\code{exp(log_lik)}) of each observation. This is related to
 the relative efficiency of estimating the normalizing term in
-self-normalizing importance sampling when using posterior draws obtained
+self-normalized importance sampling when using posterior draws obtained
 with MCMC. If MCMC draws are used and \code{r_eff} is not provided then
 the reported PSIS effective sample sizes and Monte Carlo error estimates
-will be over-optimistic. If the posterior draws are independent then
-\code{r_eff=1} and can be omitted. The warning message thrown when \code{r_eff} is
-not specified can be disabled by setting \code{r_eff} to \code{NA}. See the
-\code{\link[loo:relative_eff]{relative_eff()}} helper functions for computing \code{r_eff}.}
+can be over-optimistic. If the posterior draws are (near) independent then
+\code{r_eff=1} can be used. \code{r_eff} has to be a scalar (same value is used
+for all observations) or a vector with length equal to the number of
+observations. The default value is 1. See the \code{\link[loo:relative_eff]{relative_eff()}} helper
+functions for help computing \code{r_eff}.}
 
 \item{method}{A vector of model fit methods to evaluate and add to the model
 object.}
diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml
index 6b1312d..8374181 100644
--- a/pkgdown/_pkgdown.yml
+++ b/pkgdown/_pkgdown.yml
@@ -79,6 +79,8 @@ reference:
 - contents:
   - measr_dcm
   - measrfit-class
+  - measrfit
+  - as_measrfit
 
 - title: Model evaluation
 
diff --git a/tests/testthat/test-mcmc.R b/tests/testthat/test-mcmc.R
index 4f7bf17..f8cd29a 100644
--- a/tests/testthat/test-mcmc.R
+++ b/tests/testthat/test-mcmc.R
@@ -29,6 +29,11 @@ if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
   )
 }
 
+test_that("validation works", {
+  expect_identical(validate_measrfit(cmds_mdm_lcdm), cmds_mdm_lcdm)
+  expect_identical(validate_measrfit(cmds_mdm_dina), cmds_mdm_dina)
+})
+
 test_that("as_draws works", {
   skip_on_cran()
 
diff --git a/tests/testthat/test-measrfit-class.R b/tests/testthat/test-measrfit-class.R
new file mode 100644
index 0000000..22404dc
--- /dev/null
+++ b/tests/testthat/test-measrfit-class.R
@@ -0,0 +1,34 @@
+test_that("validation works", {
+  expect_identical(validate_measrfit(rstn_dina), rstn_dina)
+  expect_identical(validate_measrfit(rstn_dino), rstn_dino)
+})
+
+test_that("creation works", {
+  expect_identical(
+    rstn_dina,
+    measrfit(
+      data = rstn_dina$data,
+      type = rstn_dina$type,
+      prior = rstn_dina$prior,
+      stancode = rstn_dina$stancode,
+      method = rstn_dina$method,
+      algorithm = rstn_dina$algorithm,
+      backend = rstn_dina$backend,
+      model = rstn_dina$model,
+      respondent_estimates = rstn_dina$respondent_estimates,
+      fit = rstn_dina$fit,
+      criteria = rstn_dina$criteria,
+      reliability = rstn_dina$reliability,
+      file = rstn_dina$file,
+      version = rstn_dina$version,
+      class = "measrdcm"
+    )
+  )
+})
+
+test_that("coercion works", {
+  expect_identical(
+    rstn_dino,
+    as_measrfit(rstn_dino, class = "measrdcm")
+  )
+})
diff --git a/vignettes/articles/fits/ecpe-lcdm.rds b/vignettes/articles/fits/ecpe-lcdm.rds
index a57f138..e0432e2 100644
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diff --git a/vignettes/fits/ecpe-optim-lcdm.rds b/vignettes/fits/ecpe-optim-lcdm.rds
index 0b157a6..3fcfee1 100644
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