diff --git a/R/surv-roc_auc_survival.R b/R/surv-roc_auc_survival.R
index 791c389e..c0f1bea7 100644
--- a/R/surv-roc_auc_survival.R
+++ b/R/surv-roc_auc_survival.R
@@ -12,7 +12,7 @@
 #' specific _evaluation times_ and, for each time, computes the area under the
 #' ROC curve. To account for censoring, inverse probability of censoring weights
 #' (IPCW) are used in the calculations. See equation 7 of section 4.3 in
-#' Blanche _at al_ (2013) for the details.
+#' Blanche _et al_ (2013) for the details.
 #'
 #' The column passed to `...` should be a list column with one element per
 #' independent experiential unit (e.g. patient). The list column should contain
diff --git a/R/surv-roc_curve_survival.R b/R/surv-roc_curve_survival.R
index 8d8a65cf..c15dc8b2 100644
--- a/R/surv-roc_curve_survival.R
+++ b/R/surv-roc_curve_survival.R
@@ -13,7 +13,7 @@
 #' This formulation takes survival probability predictions at one or more
 #' specific _evaluation times_ and, for each time, computes the ROC curve. To
 #' account for censoring, inverse probability of censoring weights (IPCW) are
-#' used in the calculations. See equation 7 of section 4.3 in Blanche _at al_
+#' used in the calculations. See equation 7 of section 4.3 in Blanche _et al_
 #' (2013) for the details.
 #'
 #' The column passed to `...` should be a list column with one element per
@@ -221,8 +221,9 @@ roc_curve_survival_impl_one <- function(event_time, delta, data, case_weights) {
 
   specificity <- vapply(
     data_split,
-    function(x)
-      sum(x$ge_time * x$weight_censored * x$case_weights, na.rm = TRUE),
+    function(x) {
+      sum(x$ge_time * x$weight_censored * x$case_weights, na.rm = TRUE)
+    },
     FUN.VALUE = numeric(1)
   )
   specificity <- cumsum(specificity)
@@ -235,11 +236,12 @@ roc_curve_survival_impl_one <- function(event_time, delta, data, case_weights) {
 
   sensitivity <- vapply(
     data_split,
-    function(x)
+    function(x) {
       sum(
         x$le_time * x$delta * x$weight_censored * x$case_weights,
         na.rm = TRUE
-      ),
+      )
+    },
     FUN.VALUE = numeric(1)
   )