diff --git a/R/p_test.R b/R/p_test.R
index c7ee4fd3..a5f5c6cf 100644
--- a/R/p_test.R
+++ b/R/p_test.R
@@ -16,9 +16,13 @@
 #' @param paired Specify whether the dataset is paired or not. Defaults to TRUE.
 #'
 #' @import dplyr
-#' @import stats
+#'
+#' @details
+#' This function is a wrapper around `wilcox.test()` from {stats}.
 #'
 #' @examples
+#' # Simulate a binary variable X
+#' # Returns a single p-value
 #' sq_data %>%
 #'   mutate(X = ifelse(Email_hours > 6, 1, 0)) %>%
 #'   p_test(outcome = "X", behavior = "External_network_size")
@@ -26,19 +30,20 @@
 
 
 
-p_test <- function(data, 
-                   outcome, 
+p_test <- function(data,
+                   outcome,
                    behavior,
                    paired = FALSE){
-  train <- data %>% 
+  train <- data %>%
     filter(!!sym(outcome) == 1 | !!sym(outcome) == 0) %>%
     select(!!sym(outcome), !!sym(behavior)) %>%
     mutate(outcome = as.character(!!sym(outcome))) %>%
     mutate(outcome = as.factor(!!sym(outcome)))
-  
-  pos <- train %>% filter(outcome == 1, na.rm=TRUE) %>% select(behavior) 
-  neg <- train %>% filter(outcome == 0, na.rm=TRUE) %>% select(behavior) 
-  
+
+  pos <- train %>% filter(outcome == 1, na.rm=TRUE) %>% select(behavior)
+  neg <- train %>% filter(outcome == 0, na.rm=TRUE) %>% select(behavior)
+
   s <- stats::wilcox.test(unlist(pos), unlist(neg), paired = paired)
+
   return(s$p.value)
-}
\ No newline at end of file
+}
diff --git a/man/p_test.Rd b/man/p_test.Rd
index ef2ac00f..c82a7f35 100644
--- a/man/p_test.Rd
+++ b/man/p_test.Rd
@@ -4,7 +4,7 @@
 \alias{p_test}
 \title{Calculate the p-value of the null hypothesis that two outcomes are from the same dataset}
 \usage{
-p_test(data, outcome, behavior)
+p_test(data, outcome, behavior, paired = FALSE)
 }
 \arguments{
 \item{data}{A Person Query dataset in the form of a data frame.}
@@ -13,8 +13,20 @@ p_test(data, outcome, behavior)
 the values 1 or 0. Used to group the two distributions.}
 
 \item{behavior}{A character vector specifying the column to be used as the behavior to test.}
+
+\item{paired}{Specify whether the dataset is paired or not. Defaults to TRUE.}
 }
 \description{
 Specify an outcome variable and return p-test outputs.
 All numeric variables in the dataset are used as predictor variables.
 }
+\details{
+This function is a wrapper around \code{wilcox.test()} from {stats}.
+}
+\examples{
+# Simulate a binary variable X
+# Returns a single p-value
+sq_data \%>\%
+  mutate(X = ifelse(Email_hours > 6, 1, 0)) \%>\%
+  p_test(outcome = "X", behavior = "External_network_size")
+}