diff --git a/NAMESPACE b/NAMESPACE
index fed80ee..2dcab1e 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -19,7 +19,6 @@ import(stringr)
 import(tidyr)
 import(tidyselect)
 importFrom(MASS,mvrnorm)
-importFrom(estimatr,lm_robust)
 importFrom(methods,is)
 importFrom(methods,new)
 importFrom(stats,setNames)
diff --git a/R/pj_estimate.R b/R/pj_estimate.R
index 3ee48de..7070179 100644
--- a/R/pj_estimate.R
+++ b/R/pj_estimate.R
@@ -4,7 +4,7 @@
 #'
 #' @import dplyr
 #' @import rlang
-#' @importFrom estimatr lm_robust
+#' @import estimatr
 #' @importFrom MASS mvrnorm
 #' @keywords internal
 #' @param .data A `projoint_data` object
@@ -17,8 +17,8 @@
 #' @param .baseline  A character vector identifying the baseline level. Its length should be 1 for profile-level analysis and 2 for choice-level analysis
 #' @param .remove_ties TRUE (default) if you want to remove ties for the attribute of interest (in profile-level analysis)
 #' @param .ignore_position TRUE if you ignore the location of profile (left or right). Relevant only if .structure == "choice_level". Defaults to NULL.
-#' @param .n_sims The number of simulations. Relevant only if .method == "simulation" 
-#' @param .n_boot The number of bootstrapped samples. Relevant only if .method == "bootstrap"
+#' @param .n_sims The number of simulations. Relevant only if .se_method == "simulation" 
+#' @param .n_boot The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"
 #' @param .weights_1 the weight to estimate IRR (see `lm_robust()`): NULL (default)
 #' @param .clusters_1 the clusters to estimate IRR (see `lm_robust()`): NULL (default)
 #' @param .se_type_1 the standard error type to estimate IRR (see `lm_robust()`): "classical" (default)
diff --git a/R/projoint.R b/R/projoint.R
index b45eb95..f0e186d 100644
--- a/R/projoint.R
+++ b/R/projoint.R
@@ -5,10 +5,10 @@
 #'
 #' @import dplyr
 #' @import rlang
+#' @import estimatr
 #' @importFrom MASS mvrnorm
 #' @importFrom methods is
 #' @importFrom methods new
-#' @importFrom estimatr lm_robust
 #' @param .data A `projoint_data` object
 #' @param .qoi A `projoint_qoi` object. If NULL, defaults to producing all MMs and all AMCEs.
 #' @param .structure Either "profile_level" or "choice_level"
@@ -19,7 +19,6 @@
 #' @param .se_method c("analytic", "simulation", "bootstrap") description
 #' @param .n_sims The number of simulations. Relevant only if .se_method == "simulation" 
 #' @param .n_boot The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"
-#' @param .n_boot The number of bootstrapped samples. Relevant only if .method == "bootstrap"
 #' @param .weights_1 the weight to estimate IRR (see `lm_robust()`): NULL (default)
 #' @param .clusters_1 the clusters to estimate IRR (see `lm_robust()`): NULL (default)
 #' @param .se_type_1 the standard error type to estimate IRR (see `lm_robust()`): "classical" (default)
diff --git a/man/pj_estimate.Rd b/man/pj_estimate.Rd
index 967b903..445ba2f 100644
--- a/man/pj_estimate.Rd
+++ b/man/pj_estimate.Rd
@@ -46,9 +46,9 @@ pj_estimate(
 
 \item{.ignore_position}{TRUE if you ignore the location of profile (left or right). Relevant only if .structure == "choice_level". Defaults to NULL.}
 
-\item{.n_sims}{The number of simulations. Relevant only if .method == "simulation"}
+\item{.n_sims}{The number of simulations. Relevant only if .se_method == "simulation"}
 
-\item{.n_boot}{The number of bootstrapped samples. Relevant only if .method == "bootstrap"}
+\item{.n_boot}{The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"}
 
 \item{.weights_1}{the weight to estimate IRR (see `lm_robust()`): NULL (default)}
 
diff --git a/man/projoint.Rd b/man/projoint.Rd
index 66588aa..2e1ac96 100644
--- a/man/projoint.Rd
+++ b/man/projoint.Rd
@@ -42,7 +42,7 @@ projoint(
 
 \item{.n_sims}{The number of simulations. Relevant only if .se_method == "simulation"}
 
-\item{.n_boot}{The number of bootstrapped samples. Relevant only if .method == "bootstrap"}
+\item{.n_boot}{The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"}
 
 \item{.weights_1}{the weight to estimate IRR (see `lm_robust()`): NULL (default)}