diff --git a/.Rbuildignore b/.Rbuildignore
index e8dae181..3cf63732 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -22,3 +22,4 @@ vignettes/benchmarks*
 ^vignettes/README
 ^vignettes/precompile.R
 ^CRAN-SUBMISSION$
+^Makefile$
diff --git a/DESCRIPTION b/DESCRIPTION
index d02b7a7d..a12e6ea6 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: hesim
 Type: Package
 Title: Health Economic Simulation Modeling and Decision Analysis
-Version: 0.5.4
+Version: 0.5.5
 Authors@R: c(
     person("Devin", "Incerti", , "devin.incerti@gmail.com", role = c("aut", "cre")),
     person("Jeroen P.", "Jansen", role = "aut"),
@@ -56,4 +56,4 @@ Suggests:
     truncnorm
 VignetteBuilder: knitr
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
diff --git a/NAMESPACE b/NAMESPACE
index f86f448a..898e0575 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -165,6 +165,7 @@ export(tpmatrix)
 export(tpmatrix_id)
 export(tpmatrix_names)
 import(data.table)
+importFrom(R6,R6Class)
 importFrom(Rcpp,evalCpp)
 importFrom(data.table,as.data.table)
 importFrom(ggplot2,.data)
diff --git a/R/ctstm.R b/R/ctstm.R
index 83349dbf..44dc8ba6 100644
--- a/R/ctstm.R
+++ b/R/ctstm.R
@@ -7,6 +7,7 @@
 #' both Markov and semi-Markov multi-state models and does not depend on the 
 #' methodology used for prediction of state probabilities. 
 #' @format An [`R6::R6Class`] object.
+#' @importFrom R6 R6Class
 #' @seealso [`create_IndivCtstmTrans()`], [`IndivCtstmTrans`]
 #' @keywords internal
 #' @export
@@ -383,7 +384,7 @@ IndivCtstmTrans <- R6::R6Class(
 #' `transition_types` in [`IndivCtstmTrans`].
 #' @inheritParams create_CohortDtstmTrans
 #' @param ... Further arguments passed to `IndivCtstmTrans$new()` in [`IndivCtstmTrans`].
-#' @return Returns an [`R6Class`] object of class [`IndivCtstmTrans`].
+#' @return Returns an [`R6::R6Class`] object of class [`IndivCtstmTrans`].
 #' @template details-create_disease_model
 #' @seealso See [`IndivCtstmTrans`] and [`IndivCtstm`] for examples.
 #' @name create_IndivCtstmTrans
diff --git a/R/hesim_data.R b/R/hesim_data.R
index 189fe795..2a0623c7 100644
--- a/R/hesim_data.R
+++ b/R/hesim_data.R
@@ -44,7 +44,7 @@ create_lines_dt <- function(strategy_list, strategy_ids = NULL){
 #' the states and transitions in a multi-state model suitable for use with [`hesim_data`]. 
 #' @param trans_mat A transition matrix in the format from the [`mstate`][mstate::mstate] package. 
 #' See [`IndivCtstmTrans`].
-#' @return Returns a [`data.table`] in tidy format with three columns:
+#' @return Returns a [`data.table::data.table`] in tidy format with three columns:
 #' \describe{
 #' \item{transition_id}{Health state transition ID.}
 #' \item{from}{The starting health state.}
@@ -729,4 +729,4 @@ get_labels <- function(object, strategy = "strategy_name",
 
   # Return
   return(l)
-}
\ No newline at end of file
+}
diff --git a/R/input_mats.R b/R/input_mats.R
index 10ad614b..16b16cd8 100644
--- a/R/input_mats.R
+++ b/R/input_mats.R
@@ -7,7 +7,7 @@
 #' (ii) [metadata][id_attributes()] used to index each matrix in `X`. 
 #' 
 #' Once created, an `input_mats` object can be converted 
-#' to a [`data.table`] with `as.data.table()`, which is a helpful way to check that 
+#' to a [`data.table::data.table`] with `as.data.table()`, which is a helpful way to check that 
 #' the object is as expected. The `print()` method summarizes the object and 
 #' prints it to the console. 
 #' 
@@ -18,7 +18,7 @@
 #' in a statistical model. May also be a list of lists of input matrices when a 
 #' list of separate models is fit (e.g., with [flexsurvreg_list()]).
 #' @param ... For `input_mats()`, arguments to pass to [id_attributes()]. For `print()`,
-#' arguments to pass to [print.data.table()].
+#' arguments to pass to [data.table::print.data.table()].
 #' 
 #' @details 
 #' `input_mats` objects are used with [`params`] objects to simulate
diff --git a/R/model-fits.R b/R/model-fits.R
index 9d9c1750..4b8b0d79 100644
--- a/R/model-fits.R
+++ b/R/model-fits.R
@@ -82,12 +82,12 @@ multinom_list <- function(...){
 #' Partitioned survival regression object
 #'
 #' Create a partitioned survival regression object of class `partsurvfit`. The object contains a list
-#' of fitted survival models fit using either \code{\link{flexsurvreg}} or \code{\link{flexsurvspline}} (i.e.,
+#' of fitted survival models fit using either \code{\link[flexsurv]{flexsurvreg}} or \code{\link[flexsurv]{flexsurvspline}} (i.e.,
 #' an object of class \code{\link{flexsurvreg_list}}) and the data frame used to perform the fit of each model. 
 #' The same data frame must have been used for each fit.  
 #' @param object An object of class \code{\link{flexsurvreg_list}}.
 #' @param data The data frame used to fit each survival model in \code{object}.
-#' \code{\link{flexsurvreg}}.  
+#' \code{\link[flexsurv]{flexsurvreg}}.  
 #' @return Returns an object of class `partsurvfit`, which is a list containing two elements. 
 #' The first element, "models", contains the survival models passed to \code{object}, and the second 
 #' element, "data" contains the data frame passed to \code{data}.
@@ -112,4 +112,4 @@ partsurvfit <- function(object, data){
   res <- list(models = object, data = data)
   class(res) <- "partsurvfit"
   return(res)
-}
\ No newline at end of file
+}
diff --git a/R/model_def.R b/R/model_def.R
index 3202aef4..e4087194 100644
--- a/R/model_def.R
+++ b/R/model_def.R
@@ -123,7 +123,7 @@ c.eval_rng <- function(...) {
 #' character string used to separate the terms.
 #' @param ... For the print method, arguments to pass to `summary.eval_rng()`. 
 #' 
-#' @return `summary.eval_rng()` returns a [`data.table`] with columns for
+#' @return `summary.eval_rng()` returns a [`data.table::data.table`] with columns for
 #' (i) the name of the parameter (`param`), (ii) the mean of the parameter
 #' samples (`mean`), (iii) the standard deviation of the parameter samples (`sd`),
 #' and (iv) quantiles of the parameter samples corresponding
diff --git a/R/params.R b/R/params.R
index 46aa21ff..23384e74 100644
--- a/R/params.R
+++ b/R/params.R
@@ -22,7 +22,7 @@ NULL
 #' computed.
 #' @param ... Additional arguments affecting the summary. Currently unused. 
 #' 
-#' @return A [`data.table`] that always contains the following columns:
+#' @return A [`data.table::data.table`] that always contains the following columns:
 #' \describe{
 #' \item{term}{The regression term.}
 #' \item{mean}{The mean value of the regression term.}
diff --git a/R/plot.R b/R/plot.R
index 67ee26a9..ddcc18f2 100644
--- a/R/plot.R
+++ b/R/plot.R
@@ -6,7 +6,7 @@ format_dollar <- function(x) {
 # Cost-effectiveness plane -----------------------------------------------------
 #' Plot cost-effectiveness plane
 #' 
-#' Plot a cost-effectiveness plane from the output of [`cea_pw()`] using [`ggplot2`]. 
+#' Plot a cost-effectiveness plane from the output of [`cea_pw()`] using [`ggplot2::ggplot`]. 
 #' Each point is a random draw of incremental costs (y-axis) and incremental QALYs (x-axis)
 #' from a probabilistic sensitivity analysis.
 #' @inheritParams set_labels
@@ -69,7 +69,7 @@ plot_ceplane <- function(x, k = 50000, labels = NULL) {
 #' Plot cost-effectiveness acceptability curve
 #' 
 #' Plot a cost-effectiveness curve from either the output of [`cea()`] or
-#' [`cea_pw()`] using [`ggplot2`]. The former compares all treatment strategies
+#' [`cea_pw()`] using [`ggplot2::ggplot`]. The former compares all treatment strategies
 #' simultaneously and uses the probabilistic sensitivity analysis (PSA) to compute
 #' the probability that each strategy is the most cost-effective at a given 
 #' willingness to pay value, while the latter uses the PSA to compute the probability
@@ -154,7 +154,7 @@ plot_ceac.cea <- function(x, labels = NULL, ...) {
 #' Plot cost-effectiveness acceptability frontier
 #' 
 #' Plot a cost-effectiveness acceptability frontier (CEAF) from the output of 
-#' [`cea`] using [`ggplot2`]. The CEAF plots the probability
+#' [`cea`] using [`ggplot2::ggplot`]. The CEAF plots the probability
 #' that the optimal treatment strategy (i.e., the strategy with the highest 
 #' expected net monetary benefit) is cost-effective. 
 #' @inheritParams set_labels
@@ -172,7 +172,7 @@ plot_ceaf <- function(x, labels = NULL) {
 #' Plot expected value of perfect information
 #' 
 #' Plot the expected value of perfect information (EVPI) from the output of 
-#' [`cea()`] using [`ggplot2`]. Intuitively, the EVPI provides an estimate of the 
+#' [`cea()`] using [`ggplot2::ggplot`]. Intuitively, the EVPI provides an estimate of the 
 #' amount that a decision maker would be willing to pay to collect additional data 
 #' and completely eliminate uncertainty.
 #' @inheritParams set_labels
diff --git a/R/statevals.R b/R/statevals.R
index 189c40b4..e9e043fc 100644
--- a/R/statevals.R
+++ b/R/statevals.R
@@ -361,7 +361,7 @@ create_StateVals.lm <- function(object, input_data = NULL, n = 1000,
   return(StateVals$new(params = params, input_data = input_mats, ...))
 }
 
-#' @rdname create_StateVals 
+#' @rdname create_StateVals
 #' @export
 create_StateVals.stateval_tbl <- function(object, hesim_data = NULL, n = 1000, ...){
   
diff --git a/R/tparams_transprobs.R b/R/tparams_transprobs.R
index 3496d049..88fe5910 100644
--- a/R/tparams_transprobs.R
+++ b/R/tparams_transprobs.R
@@ -347,7 +347,7 @@ summarize_transprobs_dt <- function(x, probs, unflatten,
 #' @inheritParams summary.tpmatrix
 #' @param object A [`tparams_transprobs`] object.
 #' 
-#' @return If `unflatten = "FALSE"` (the default), then a [`data.table`]
+#' @return If `unflatten = "FALSE"` (the default), then a [`data.table::data.table`]
 #' is returned with columns for (i) the health state that is being transitioned
 #' from (`from`), (ii) the health state that is being transitioned to (`to`)
 #' (iii) the mean of each parameter across parameter samples (`mean`),
@@ -462,4 +462,4 @@ as.data.table.tparams_transprobs <- function(x, ..., prefix = "prob_", sep = "_"
     setattr(x_dt, v, x[[v]])
   }
   x_dt[, ]
-}
\ No newline at end of file
+}
diff --git a/R/tpmatrix.R b/R/tpmatrix.R
index 44077178..b6334e9b 100644
--- a/R/tpmatrix.R
+++ b/R/tpmatrix.R
@@ -339,7 +339,7 @@ tpmatrix <- function(..., complement = NULL, states = NULL,
 #' vectors. See "Value" below for additional details.
 #' @param ... Additional arguments affecting the summary. Currently unused.
 #' 
-#' @return If `unflatten = "FALSE"` (the default), then a [`data.table`]
+#' @return If `unflatten = "FALSE"` (the default), then a [`data.table::data.table`]
 #' is returned with columns for (i) the health state that is being transitioned
 #' from (`from`), (ii) the health state that is being transitioned to (`to`)
 #' (iii) the mean of each parameter across parameter samples (`mean`),
@@ -769,4 +769,4 @@ apply_rr <- function(x, rr, index, complement = NULL) {
   
   # Run C function
   C_apply_rr(x, rr, index - 1, complement - 1)
-}
\ No newline at end of file
+}
diff --git a/README.Rmd b/README.Rmd
index a8be236c..5145887e 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -51,7 +51,7 @@ library("knitr")
 library("kableExtra")
 level <- c("Cohort", "Cohort", "Cohort", "Cohort", "Individual", "Individual", "Cohort")
 links <- c(
-  rep("https://arxiv.org/pdf/2102.09437.pdf", 3),
+  rep("https://arxiv.org/pdf/2102.09437", 3),
   "https://hesim-dev.github.io/hesim/articles/markov-cohort.html",
   "https://hesim-dev.github.io/hesim/articles/markov-inhomogeneous-cohort.html",
   "https://hesim-dev.github.io/hesim/articles/mlogit.html",
@@ -100,4 +100,4 @@ If you use `hesim`, please cite as follows:
 
 ```{r, echo = FALSE, comment = ""}
 citation("hesim")
-```
\ No newline at end of file
+```
diff --git a/README.md b/README.md
index b48beb85..f0644762 100644
--- a/README.md
+++ b/README.md
@@ -136,7 +136,7 @@ Application
 1
 </td>
 <td style="text-align:left;width: 15em; ">
-<a href="https://arxiv.org/pdf/2102.09437.pdf" style="     ">Preprint
+<a href="https://arxiv.org/pdf/2102.09437" style="     ">Preprint
 4.1</a>
 </td>
 <td style="text-align:left;">
@@ -163,7 +163,7 @@ Oncology
 2
 </td>
 <td style="text-align:left;width: 15em; ">
-<a href="https://arxiv.org/pdf/2102.09437.pdf" style="     ">Preprint
+<a href="https://arxiv.org/pdf/2102.09437" style="     ">Preprint
 4.2</a>
 </td>
 <td style="text-align:left;">
@@ -190,7 +190,7 @@ Oncology
 3
 </td>
 <td style="text-align:left;width: 15em; ">
-<a href="https://arxiv.org/pdf/2102.09437.pdf" style="     ">Preprint
+<a href="https://arxiv.org/pdf/2102.09437" style="     ">Preprint
 4.3</a>
 </td>
 <td style="text-align:left;">
diff --git a/man/create_IndivCtstmTrans.Rd b/man/create_IndivCtstmTrans.Rd
index 1789c2e4..dd7a472b 100644
--- a/man/create_IndivCtstmTrans.Rd
+++ b/man/create_IndivCtstmTrans.Rd
@@ -79,7 +79,7 @@ distribution. If \code{"none"}, then only point estimates are returned.}
 \code{transition_types} in \code{\link{IndivCtstmTrans}}.}
 }
 \value{
-Returns an \code{\link{R6Class}} object of class \code{\link{IndivCtstmTrans}}.
+Returns an \code{\link[R6:R6Class]{R6::R6Class}} object of class \code{\link{IndivCtstmTrans}}.
 }
 \description{
 A generic function for creating an object of class \code{\link{IndivCtstmTrans}}.
diff --git a/man/create_trans_dt.Rd b/man/create_trans_dt.Rd
index 73ea1c10..28dc6462 100644
--- a/man/create_trans_dt.Rd
+++ b/man/create_trans_dt.Rd
@@ -11,7 +11,7 @@ create_trans_dt(trans_mat)
 See \code{\link{IndivCtstmTrans}}.}
 }
 \value{
-Returns a \code{\link{data.table}} in tidy format with three columns:
+Returns a \code{\link[data.table:data.table]{data.table::data.table}} in tidy format with three columns:
 \describe{
 \item{transition_id}{Health state transition ID.}
 \item{from}{The starting health state.}
diff --git a/man/hesim.Rd b/man/hesim.Rd
index 1624297c..6bd5d20a 100644
--- a/man/hesim.Rd
+++ b/man/hesim.Rd
@@ -2,8 +2,8 @@
 % Please edit documentation in R/hesim.R
 \docType{package}
 \name{hesim}
-\alias{hesim}
 \alias{hesim-package}
+\alias{hesim}
 \title{hesim: Health Economic Simulation Modeling and Decision Analysis}
 \description{
 To learn more about \code{hesim} visit the \href{https://hesim-dev.github.io/hesim/}{website}.
diff --git a/man/input_mats.Rd b/man/input_mats.Rd
index bb3e035b..8727d01f 100644
--- a/man/input_mats.Rd
+++ b/man/input_mats.Rd
@@ -18,7 +18,7 @@ in a statistical model. May also be a list of lists of input matrices when a
 list of separate models is fit (e.g., with \code{\link[=flexsurvreg_list]{flexsurvreg_list()}}).}
 
 \item{...}{For \code{input_mats()}, arguments to pass to \code{\link[=id_attributes]{id_attributes()}}. For \code{print()},
-arguments to pass to \code{\link[=print.data.table]{print.data.table()}}.}
+arguments to pass to \code{\link[data.table:print.data.table]{data.table::print.data.table()}}.}
 
 \item{x}{An \code{\link{input_mats}} object.}
 }
@@ -28,7 +28,7 @@ for simulating a statistical model. Consists of (i) input matrices, \code{X}, an
 (ii) \link[=id_attributes]{metadata} used to index each matrix in \code{X}.
 
 Once created, an \code{input_mats} object can be converted
-to a \code{\link{data.table}} with \code{as.data.table()}, which is a helpful way to check that
+to a \code{\link[data.table:data.table]{data.table::data.table}} with \code{as.data.table()}, which is a helpful way to check that
 the object is as expected. The \code{print()} method summarizes the object and
 prints it to the console.
 
diff --git a/man/partsurvfit.Rd b/man/partsurvfit.Rd
index 4f9939e6..0f165ec9 100644
--- a/man/partsurvfit.Rd
+++ b/man/partsurvfit.Rd
@@ -10,7 +10,7 @@ partsurvfit(object, data)
 \item{object}{An object of class \code{\link{flexsurvreg_list}}.}
 
 \item{data}{The data frame used to fit each survival model in \code{object}.
-\code{\link{flexsurvreg}}.}
+\code{\link[flexsurv]{flexsurvreg}}.}
 }
 \value{
 Returns an object of class \code{partsurvfit}, which is a list containing two elements.
@@ -19,7 +19,7 @@ element, "data" contains the data frame passed to \code{data}.
 }
 \description{
 Create a partitioned survival regression object of class \code{partsurvfit}. The object contains a list
-of fitted survival models fit using either \code{\link{flexsurvreg}} or \code{\link{flexsurvspline}} (i.e.,
+of fitted survival models fit using either \code{\link[flexsurv]{flexsurvreg}} or \code{\link[flexsurv]{flexsurvspline}} (i.e.,
 an object of class \code{\link{flexsurvreg_list}}) and the data frame used to perform the fit of each model.
 The same data frame must have been used for each fit.
 }
diff --git a/man/plot_ceac.Rd b/man/plot_ceac.Rd
index 7cf4a1d6..2ff1a5a7 100644
--- a/man/plot_ceac.Rd
+++ b/man/plot_ceac.Rd
@@ -24,7 +24,7 @@ See the output returned by \code{\link[=get_labels]{get_labels()}} for an exampl
 }
 \description{
 Plot a cost-effectiveness curve from either the output of \code{\link[=cea]{cea()}} or
-\code{\link[=cea_pw]{cea_pw()}} using \code{\link{ggplot2}}. The former compares all treatment strategies
+\code{\link[=cea_pw]{cea_pw()}} using \code{\link[ggplot2:ggplot]{ggplot2::ggplot}}. The former compares all treatment strategies
 simultaneously and uses the probabilistic sensitivity analysis (PSA) to compute
 the probability that each strategy is the most cost-effective at a given
 willingness to pay value, while the latter uses the PSA to compute the probability
diff --git a/man/plot_ceaf.Rd b/man/plot_ceaf.Rd
index a049e194..c0336e6f 100644
--- a/man/plot_ceaf.Rd
+++ b/man/plot_ceaf.Rd
@@ -19,7 +19,7 @@ A \code{ggplot} object.
 }
 \description{
 Plot a cost-effectiveness acceptability frontier (CEAF) from the output of
-\code{\link{cea}} using \code{\link{ggplot2}}. The CEAF plots the probability
+\code{\link{cea}} using \code{\link[ggplot2:ggplot]{ggplot2::ggplot}}. The CEAF plots the probability
 that the optimal treatment strategy (i.e., the strategy with the highest
 expected net monetary benefit) is cost-effective.
 }
diff --git a/man/plot_ceplane.Rd b/man/plot_ceplane.Rd
index c07b5a8a..958c1d5e 100644
--- a/man/plot_ceplane.Rd
+++ b/man/plot_ceplane.Rd
@@ -20,7 +20,7 @@ See the output returned by \code{\link[=get_labels]{get_labels()}} for an exampl
 A \code{ggplot} object.
 }
 \description{
-Plot a cost-effectiveness plane from the output of \code{\link[=cea_pw]{cea_pw()}} using \code{\link{ggplot2}}.
+Plot a cost-effectiveness plane from the output of \code{\link[=cea_pw]{cea_pw()}} using \code{\link[ggplot2:ggplot]{ggplot2::ggplot}}.
 Each point is a random draw of incremental costs (y-axis) and incremental QALYs (x-axis)
 from a probabilistic sensitivity analysis.
 }
diff --git a/man/plot_evpi.Rd b/man/plot_evpi.Rd
index dd275cdd..f27f221a 100644
--- a/man/plot_evpi.Rd
+++ b/man/plot_evpi.Rd
@@ -19,7 +19,7 @@ A \code{ggplot} object.
 }
 \description{
 Plot the expected value of perfect information (EVPI) from the output of
-\code{\link[=cea]{cea()}} using \code{\link{ggplot2}}. Intuitively, the EVPI provides an estimate of the
+\code{\link[=cea]{cea()}} using \code{\link[ggplot2:ggplot]{ggplot2::ggplot}}. Intuitively, the EVPI provides an estimate of the
 amount that a decision maker would be willing to pay to collect additional data
 and completely eliminate uncertainty.
 }
diff --git a/man/plugin.Rd b/man/plugin.Rd
index 372a1892..9f0d879d 100644
--- a/man/plugin.Rd
+++ b/man/plugin.Rd
@@ -13,17 +13,17 @@ inlineCxxPlugin(...)
 Code to use the hesim package inline. Not directly called by the user.
 }
 \examples{
-library(Rcpp)
-sourceCpp(code="
-// [[Rcpp::depends(hesim)]]
-// [[Rcpp::depends(RcppArmadillo)]]
-#include <hesim/stats/distributions.h>
-// [[Rcpp::export]]
-double test_inline_gengamma(double mu, double sigma, double Q) {
-  hesim::stats::gengamma gg(mu, sigma, Q);
-  return gg.random();
-}")
-set.seed(12345)
-test_inline_gengamma(1.0, 1.0, 1.0)
+  library(Rcpp)
+  sourceCpp(code="
+  // [[Rcpp::depends(hesim)]]
+  // [[Rcpp::depends(RcppArmadillo)]]
+  #include <hesim.h>
+  // [[Rcpp::export]]
+  double test_inline_gengamma(double mu, double sigma, double Q) {
+    hesim::stats::gengamma gg(mu, sigma, Q);
+    return gg.random();
+  }")
+  set.seed(12345)
+  test_inline_gengamma(1.0, 1.0, 1.0)
 }
 \keyword{internal}
diff --git a/man/summary.eval_rng.Rd b/man/summary.eval_rng.Rd
index 802d426f..17c4a30b 100644
--- a/man/summary.eval_rng.Rd
+++ b/man/summary.eval_rng.Rd
@@ -23,7 +23,7 @@ character string used to separate the terms.}
 \item{...}{For the print method, arguments to pass to \code{summary.eval_rng()}.}
 }
 \value{
-\code{summary.eval_rng()} returns a \code{\link{data.table}} with columns for
+\code{summary.eval_rng()} returns a \code{\link[data.table:data.table]{data.table::data.table}} with columns for
 (i) the name of the parameter (\code{param}), (ii) the mean of the parameter
 samples (\code{mean}), (iii) the standard deviation of the parameter samples (\code{sd}),
 and (iv) quantiles of the parameter samples corresponding
diff --git a/man/summary.params.Rd b/man/summary.params.Rd
index 60652061..c7d0ca0e 100644
--- a/man/summary.params.Rd
+++ b/man/summary.params.Rd
@@ -30,7 +30,7 @@ computed.}
 \item{...}{Additional arguments affecting the summary. Currently unused.}
 }
 \value{
-A \code{\link{data.table}} that always contains the following columns:
+A \code{\link[data.table:data.table]{data.table::data.table}} that always contains the following columns:
 \describe{
 \item{term}{The regression term.}
 \item{mean}{The mean value of the regression term.}
diff --git a/man/summary.tparams_transprobs.Rd b/man/summary.tparams_transprobs.Rd
index 88f7e7ba..377ff88d 100644
--- a/man/summary.tparams_transprobs.Rd
+++ b/man/summary.tparams_transprobs.Rd
@@ -23,7 +23,7 @@ vectors. See "Value" below for additional details.}
 \item{...}{Additional arguments affecting the summary. Currently unused.}
 }
 \value{
-If \code{unflatten = "FALSE"} (the default), then a \code{\link{data.table}}
+If \code{unflatten = "FALSE"} (the default), then a \code{\link[data.table:data.table]{data.table::data.table}}
 is returned with columns for (i) the health state that is being transitioned
 from (\code{from}), (ii) the health state that is being transitioned to (\code{to})
 (iii) the mean of each parameter across parameter samples (\code{mean}),
diff --git a/man/summary.tpmatrix.Rd b/man/summary.tpmatrix.Rd
index 92418f29..7f774c05 100644
--- a/man/summary.tpmatrix.Rd
+++ b/man/summary.tpmatrix.Rd
@@ -27,7 +27,7 @@ vectors. See "Value" below for additional details.}
 \item{...}{Additional arguments affecting the summary. Currently unused.}
 }
 \value{
-If \code{unflatten = "FALSE"} (the default), then a \code{\link{data.table}}
+If \code{unflatten = "FALSE"} (the default), then a \code{\link[data.table:data.table]{data.table::data.table}}
 is returned with columns for (i) the health state that is being transitioned
 from (\code{from}), (ii) the health state that is being transitioned to (\code{to})
 (iii) the mean of each parameter across parameter samples (\code{mean}),