diff --git a/_manuscript/L2_VWP_webcam_ET.qmd b/_manuscript/L2_VWP_webcam_ET.qmd
index bfc774f..fce7b7c 100644
--- a/_manuscript/L2_VWP_webcam_ET.qmd
+++ b/_manuscript/L2_VWP_webcam_ET.qmd
@@ -119,7 +119,7 @@ language:
   title-block-correspondence-note: "Correspondence concerning this article should be addressed to"
   title-block-role-introduction: "Author roles were classified using the Contributor Role Taxonomy (CRediT; https://credit.niso.org/) as follows:"
 format:
-  apaquarto-pdf: default
+  apaquarto-docx: default
 execute: 
   echo: true
   warning: false
@@ -137,7 +137,6 @@ execute:
 #| echo: false
 
 library(knitr)
-library(formatR)
 
 opts_chunk$set(fig.align='center', size="small", tidy.opts=list(width.cutoff=60), tidy=TRUE)
 
@@ -397,6 +396,8 @@ Once this is installed, `webgazeR` can be loaded along with additional useful pa
 
 ```{r}
 #| label: packages
+
+
 options(stringsAsFactors = FALSE) # no automatic data transformation
 options("scipen" = 100, "digits" = 10) # suppress math annotation
 
@@ -473,35 +474,36 @@ First, we will create a cleaned up version of our use the behavioral, trial-leve
 It is important to note here that what the behavioral spreadsheet denotes as trial is not in fact the trial number used in the eye-tracking files. Thus it is imperative you use `spreadhseet row` as trial number to merge the two files successfully.
 
 ```{r}
-#|message: false
-#|echo: true
 eye_behav_L2 <- L2_data %>%
  
   janitor::clean_names() %>%
  
   # Select specific columns to keep in the dataset
-  dplyr::select(participant_private_id,  correct, tlpic, trpic, blpic, brpic, condition, eng_targetword, targetword, typetl, typetr, typebl, typebr, zone_name, zone_type,reaction_time, spreadsheet_row,  response) %>%
+  dplyr::select(participant_private_id, correct, tlpic, trpic, blpic, brpic, condition, 
+                eng_targetword, targetword, typetl, typetr, typebl, typebr, zone_name, 
+                zone_type, reaction_time, spreadsheet_row, response) %>%
  
   # Filter the rows where 'Zone.Type' equals "response_button_image"
   dplyr::filter(zone_type == "response_button_image") %>%
  
   # Rename columns for easier use and readability
   dplyr::rename(
-    "TL" = "tlpic",              # Rename 'tlpic' to 'TL'
-    "TR" = "trpic",             # Rename 'trpic' to 'TR'
-    "BL" = "blpic",            # Rename 'blpic' to 'BL'
-    "BR" = "brpic",                # Rename 'brpic' to 'BR'
-    "targ_loc" = "zone_name",       # Rename 'Zone.Name' to 'targ_loc'
-    "subject" = "participant_private_id",  # Rename 'Participant.Private.ID' to 'subject'
-    "trial" = "spreadsheet_row",    # Rename 'spreadsheet_row' to 'trial'
-    "acc" = "correct",              # Rename 'Correct' to 'acc' (accuracy)
-    "RT" = "reaction_time"          # Rename 'Reaction.Time' to 'RT'
+    TL = tlpic,             # Rename 'tlpic' to 'TL'
+    TR = trpic,             # Rename 'trpic' to 'TR'
+    BL = blpic,             # Rename 'blpic' to 'BL'
+    BR = brpic,             # Rename 'brpic' to 'BR'
+    targ_loc = zone_name,   # Rename 'zone_name' to 'targ_loc'
+    subject = participant_private_id,  # Rename 'participant_private_id' to 'subject'
+    trial = spreadsheet_row,  # Rename 'spreadsheet_row' to 'trial'
+    acc = correct,          # Rename 'correct' to 'acc' (accuracy)
+    RT = reaction_time      # Rename 'reaction_time' to 'RT'
   ) %>%
  
   # Convert the 'RT' (Reaction Time) column to numeric type
-  mutate(RT = as.numeric(RT),
-         subject=as.factor(subject),
-         trial=as.factor(trial))
+  dplyr::mutate(RT = as.numeric(RT),
+                subject = as.factor(subject),
+                trial = as.factor(trial))
+
 
 ```