diff --git a/DESCRIPTION b/DESCRIPTION
index 6b2e8d1..ed9953c 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,13 +1,14 @@
 Package: REDCapRITS
-Title: REDCap Repeating Instrument Table Splitter
+Title: REDCap Repeating Instrument Table Splitter Fork
 Version: 0.2.2.1
 Authors@R: c(
-    person("Paul", "Egeler", email = "paul.egeler@spectrumhealth.org", role = c("aut", "cre")),
-    person("Spectrum Health, Grand Rapids, MI", role = "cph"),
-     person("Andreas Gammelgaard", "Damsbo", , "agdamsbo@clin.au.dk", role = c("ctb"),
+    person("Paul", "Egeler", email = "paul.egeler@spectrumhealth.org", role = c("aut")),
+     person("Andreas Gammelgaard", "Damsbo", email = "agdamsbo@clin.au.dk", role = c("cre", "ctb","cph"),
            comment = c(ORCID = "0000-0002-7559-1154")))
 Copyright: Spectrum Health, Grand Rapids, MI
-Description: Split REDCap repeating instruments output into multiple tables. 
+Description: This is a fork of REDCapRITS by Paul Egeler and Spectrum Health. See
+    [https://github.com/SpectrumHealthResearch/REDCapRITS](https://github.com/SpectrumHealthResearch/REDCapRITS).
+    Split REDCap repeating instruments output into multiple tables. 
     This will take raw output from a REDCap export and split it into a base table
     and child tables for each repeating instrument. 
     REDCap (Research Electronic Data Capture) is a secure, web-based software
@@ -29,8 +30,8 @@ License: GPL-3
 Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.2.3
-URL: https://github.com/SpectrumHealthResearch/REDCapRITS
-BugReports: https://github.com/SpectrumHealthResearch/REDCapRITS/issues
+URL: https://github.com/agdamsbo/REDCapRITS
+BugReports: https://github.com/agdamsbo/REDCapRITS/issues
 Collate: 
     'utils.r'
     'process_user_input.r'
diff --git a/R/REDCap_split.r b/R/REDCap_split.r
index 3f516ac..7662445 100644
--- a/R/REDCap_split.r
+++ b/R/REDCap_split.r
@@ -82,12 +82,11 @@
 REDCap_split <- function(records,
                          metadata,
                          primary_table_name = "",
-                         forms = c("repeating", "all")
-) {
-
+                         forms = c("repeating", "all")) {
   # Process user input
   records  <- process_user_input(records)
-  metadata <- as.data.frame(process_user_input(metadata)) # See issue #12
+  metadata <-
+    as.data.frame(process_user_input(metadata)) # See issue #12
 
   # Get the variable names in the dataset
   vars_in_data <- names(records)
@@ -96,12 +95,13 @@ REDCap_split <- function(records,
   forms <- match.arg(forms)
 
   # Check to see if there were any repeating instruments
-  if (forms == "repeating" && !"redcap_repeat_instrument" %in% vars_in_data) {
+  if (forms == "repeating" &&
+      !"redcap_repeat_instrument" %in% vars_in_data) {
     stop("There are no repeating instruments in this dataset.")
   }
 
   # Remove NAs from `redcap_repeat_instrument` (see issue #12)
-  if(any(is.na(records$redcap_repeat_instrument))) {
+  if (any(is.na(records$redcap_repeat_instrument))) {
     records$redcap_repeat_instrument <- ifelse(
       is.na(records$redcap_repeat_instrument),
       "",
@@ -113,7 +113,8 @@ REDCap_split <- function(records,
   names(metadata) <- metadata_names
 
   # Make sure that no metadata columns are factors
-  metadata <- rapply(metadata, as.character, classes = "factor", how = "replace")
+  metadata <-
+    rapply(metadata, as.character, classes = "factor", how = "replace")
 
   # Find the fields and associated form
   fields <- match_fields_to_form(metadata, vars_in_data)
@@ -131,22 +132,23 @@ REDCap_split <- function(records,
 
   if ("redcap_repeat_instrument" %in% vars_in_data) {
     # Variables to be at the beginning of each repeating instrument
-    repeat_instrument_fields <- grep(
-      "^redcap_repeat.*",
-      vars_in_data,
-      value = TRUE
-    )
+    repeat_instrument_fields <- grep("^redcap_repeat.*",
+                                     vars_in_data,
+                                     value = TRUE)
 
     # Identify the subtables in the data
     subtables <- unique(records$redcap_repeat_instrument)
     subtables <- subtables[subtables != ""]
 
     # Split the table based on instrument
-    out <- split.data.frame(records, records$redcap_repeat_instrument)
+    out <-
+      split.data.frame(records, records$redcap_repeat_instrument)
     primary_table_index <- which(names(out) == "")
 
     if (forms == "repeating" && primary_table_name %in% subtables) {
-      warning("The label given to the primary table is already used by a repeating instrument. The primary table label will be left blank.")
+      warning(
+        "The label given to the primary table is already used by a repeating instrument. The primary table label will be left blank."
+      )
       primary_table_name <- ""
     } else if (primary_table_name > "") {
       names(out)[[primary_table_index]] <- primary_table_name
@@ -154,26 +156,16 @@ REDCap_split <- function(records,
 
     # Delete the variables that are not relevant
     for (i in names(out)) {
-
       if (i == primary_table_name) {
-
-        out_fields <- which(
-          vars_in_data %in% c(
-            universal_fields,
-            fields[!fields[,2] %in% subtables, 1]
-          )
-        )
-        out[[primary_table_index]] <- out[[primary_table_index]][out_fields]
+        out_fields <- which(vars_in_data %in% c(universal_fields,
+                                                fields[!fields[, 2] %in% subtables, 1]))
+        out[[primary_table_index]] <-
+          out[[primary_table_index]][out_fields]
 
       } else {
-
-        out_fields <- which(
-          vars_in_data %in% c(
-            universal_fields,
-            repeat_instrument_fields,
-            fields[fields[,2] == i, 1]
-          )
-        )
+        out_fields <- which(vars_in_data %in% c(universal_fields,
+                                                repeat_instrument_fields,
+                                                fields[fields[, 2] == i, 1]))
         out[[i]] <- out[[i]][out_fields]
 
       }
@@ -181,20 +173,14 @@ REDCap_split <- function(records,
     }
 
     if (forms == "all") {
-
-      out <- c(
-        split_non_repeating_forms(
-          out[[primary_table_index]],
-          universal_fields,
-          fields[!fields[,2] %in% subtables,]
-        ),
-        out[-primary_table_index]
-      )
+      out <- c(split_non_repeating_forms(out[[primary_table_index]],
+                                         universal_fields,
+                                         fields[!fields[, 2] %in% subtables, ]),
+               out[-primary_table_index])
 
     }
 
   } else {
-
     out <- split_non_repeating_forms(records, universal_fields, fields)
 
   }
diff --git a/R/process_user_input.r b/R/process_user_input.r
index fe6de68..0ca2aae 100644
--- a/R/process_user_input.r
+++ b/R/process_user_input.r
@@ -17,7 +17,6 @@ process_user_input.data.frame <- function(x, ...) {
 }
 
 process_user_input.character <- function(x, ...) {
-
   if (!requireNamespace("jsonlite", quietly = TRUE)) {
     stop(
       "The package 'jsonlite' is needed to convert ",
@@ -35,7 +34,6 @@ process_user_input.character <- function(x, ...) {
 }
 
 process_user_input.response <- function(x, ...) {
-
   process_user_input(rawToChar(x$content))
 
 }
diff --git a/R/utils.r b/R/utils.r
index 87d1509..9216f64 100644
--- a/R/utils.r
+++ b/R/utils.r
@@ -1,9 +1,6 @@
 match_fields_to_form <- function(metadata, vars_in_data) {
-
-  fields <- metadata[
-    !metadata$field_type %in% c("descriptive", "checkbox"),
-    c("field_name", "form_name")
-  ]
+  fields <- metadata[!metadata$field_type %in% c("descriptive", "checkbox"),
+                     c("field_name", "form_name")]
 
   # Process instrument status fields
   form_names <- unique(metadata$form_name)
@@ -16,9 +13,9 @@ match_fields_to_form <- function(metadata, vars_in_data) {
   fields <- rbind(fields, form_complete_fields)
 
   # Process survey timestamps
-  timestamps <- intersect(vars_in_data, paste0(form_names, "_timestamp"))
+  timestamps <-
+    intersect(vars_in_data, paste0(form_names, "_timestamp"))
   if (length(timestamps)) {
-
     timestamp_fields <- data.frame(
       field_name = timestamps,
       form_name = sub("_timestamp$", "", timestamps),
@@ -31,28 +28,21 @@ match_fields_to_form <- function(metadata, vars_in_data) {
 
   # Process checkbox fields
   if (any(metadata$field_type == "checkbox")) {
-
-    checkbox_basenames <- metadata[
-      metadata$field_type == "checkbox",
-      c("field_name", "form_name")
-    ]
+    checkbox_basenames <- metadata[metadata$field_type == "checkbox",
+                                   c("field_name", "form_name")]
 
     checkbox_fields <-
-      do.call(
-        "rbind",
-        apply(
-          checkbox_basenames,
-          1,
-          function(x, y)
-            data.frame(
-              field_name = y[grepl(paste0("^", x[1], "___((?!\\.factor).)+$"), y, perl = TRUE)],
-              form_name = x[2],
-              stringsAsFactors = FALSE,
-              row.names = NULL
-            ),
-          y = vars_in_data
-        )
-      )
+      do.call("rbind",
+              apply(checkbox_basenames,
+                    1,
+                    function(x, y)
+                      data.frame(
+                        field_name = y[grepl(paste0("^", x[1], "___((?!\\.factor).)+$"), y, perl = TRUE)],
+                        form_name = x[2],
+                        stringsAsFactors = FALSE,
+                        row.names = NULL
+                      ),
+                    y = vars_in_data))
 
     fields <- rbind(fields, checkbox_fields)
 
@@ -60,26 +50,21 @@ match_fields_to_form <- function(metadata, vars_in_data) {
 
   # Process ".*\\.factor" fields supplied by REDCap's export data R script
   if (any(grepl("\\.factor$", vars_in_data))) {
-
     factor_fields <-
-      do.call(
-        "rbind",
-        apply(
-          fields,
-          1,
-          function(x, y) {
-            field_indices <- grepl(paste0("^", x[1], "\\.factor$"), y)
-            if (any(field_indices))
-              data.frame(
-                field_name = y[field_indices],
-                form_name = x[2],
-                stringsAsFactors = FALSE,
-                row.names = NULL
-              )
-          },
-          y = vars_in_data
-        )
-      )
+      do.call("rbind",
+              apply(fields,
+                    1,
+                    function(x, y) {
+                      field_indices <- grepl(paste0("^", x[1], "\\.factor$"), y)
+                      if (any(field_indices))
+                        data.frame(
+                          field_name = y[field_indices],
+                          form_name = x[2],
+                          stringsAsFactors = FALSE,
+                          row.names = NULL
+                        )
+                    },
+                    y = vars_in_data))
 
     fields <- rbind(fields, factor_fields)
 
@@ -87,20 +72,18 @@ match_fields_to_form <- function(metadata, vars_in_data) {
 
   fields
 
-  }
-
-
-split_non_repeating_forms <- function(table, universal_fields, fields) {
-
-  forms <- unique(fields[[2]])
-
-  x <- lapply(
-    forms,
-    function (x) {
-      table[names(table) %in% union(universal_fields, fields[fields[,2] == x,1])]
-  })
-
-  structure(x, names = forms)
-
 }
 
+
+split_non_repeating_forms <-
+  function(table, universal_fields, fields) {
+    forms <- unique(fields[[2]])
+
+    x <- lapply(forms,
+                function (x) {
+                  table[names(table) %in% union(universal_fields, fields[fields[, 2] == x, 1])]
+                })
+
+    structure(x, names = forms)
+
+  }
diff --git a/tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r b/tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r
index 45200aa..b9b4aa5 100644
--- a/tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r
+++ b/tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r
@@ -4,75 +4,85 @@ REDCap_process_csv <- function(data) {
     stop("This test requires the 'Hmisc' package")
   }
 
-  Hmisc::label(data$row)="Name"
-  Hmisc::label(data$redcap_repeat_instrument)="Repeat Instrument"
-  Hmisc::label(data$redcap_repeat_instance)="Repeat Instance"
-  Hmisc::label(data$mpg)="Miles/(US) gallon"
-  Hmisc::label(data$cyl)="Number of cylinders"
-  Hmisc::label(data$disp)="Displacement"
-  Hmisc::label(data$hp)="Gross horsepower"
-  Hmisc::label(data$drat)="Rear axle ratio"
-  Hmisc::label(data$wt)="Weight"
-  Hmisc::label(data$qsec)="1/4 mile time"
-  Hmisc::label(data$vs)="V engine?"
-  Hmisc::label(data$am)="Transmission"
-  Hmisc::label(data$gear)="Number of forward gears"
-  Hmisc::label(data$carb)="Number of carburetors"
-  Hmisc::label(data$color_available___red)="Colors Available (choice=Red)"
-  Hmisc::label(data$color_available___green)="Colors Available (choice=Green)"
-  Hmisc::label(data$color_available___blue)="Colors Available (choice=Blue)"
-  Hmisc::label(data$color_available___black)="Colors Available (choice=Black)"
-  Hmisc::label(data$motor_trend_cars_complete)="Complete?"
-  Hmisc::label(data$letter_group___a)="Which group? (choice=A)"
-  Hmisc::label(data$letter_group___b)="Which group? (choice=B)"
-  Hmisc::label(data$letter_group___c)="Which group? (choice=C)"
-  Hmisc::label(data$choice)="Choose one"
-  Hmisc::label(data$grouping_complete)="Complete?"
-  Hmisc::label(data$price)="Sale price"
-  Hmisc::label(data$color)="Color"
-  Hmisc::label(data$customer)="Customer Name"
-  Hmisc::label(data$sale_complete)="Complete?"
+  Hmisc::label(data$row) = "Name"
+  Hmisc::label(data$redcap_repeat_instrument) = "Repeat Instrument"
+  Hmisc::label(data$redcap_repeat_instance) = "Repeat Instance"
+  Hmisc::label(data$mpg) = "Miles/(US) gallon"
+  Hmisc::label(data$cyl) = "Number of cylinders"
+  Hmisc::label(data$disp) = "Displacement"
+  Hmisc::label(data$hp) = "Gross horsepower"
+  Hmisc::label(data$drat) = "Rear axle ratio"
+  Hmisc::label(data$wt) = "Weight"
+  Hmisc::label(data$qsec) = "1/4 mile time"
+  Hmisc::label(data$vs) = "V engine?"
+  Hmisc::label(data$am) = "Transmission"
+  Hmisc::label(data$gear) = "Number of forward gears"
+  Hmisc::label(data$carb) = "Number of carburetors"
+  Hmisc::label(data$color_available___red) = "Colors Available (choice=Red)"
+  Hmisc::label(data$color_available___green) = "Colors Available (choice=Green)"
+  Hmisc::label(data$color_available___blue) = "Colors Available (choice=Blue)"
+  Hmisc::label(data$color_available___black) = "Colors Available (choice=Black)"
+  Hmisc::label(data$motor_trend_cars_complete) = "Complete?"
+  Hmisc::label(data$letter_group___a) = "Which group? (choice=A)"
+  Hmisc::label(data$letter_group___b) = "Which group? (choice=B)"
+  Hmisc::label(data$letter_group___c) = "Which group? (choice=C)"
+  Hmisc::label(data$choice) = "Choose one"
+  Hmisc::label(data$grouping_complete) = "Complete?"
+  Hmisc::label(data$price) = "Sale price"
+  Hmisc::label(data$color) = "Color"
+  Hmisc::label(data$customer) = "Customer Name"
+  Hmisc::label(data$sale_complete) = "Complete?"
   #Setting Units
 
 
   #Setting Factors(will create new variable for factors)
-  data$redcap_repeat_instrument.factor = factor(data$redcap_repeat_instrument,levels=c("sale"))
-  data$cyl.factor = factor(data$cyl,levels=c("3","4","5","6","7","8"))
-  data$vs.factor = factor(data$vs,levels=c("1","0"))
-  data$am.factor = factor(data$am,levels=c("0","1"))
-  data$gear.factor = factor(data$gear,levels=c("3","4","5"))
-  data$carb.factor = factor(data$carb,levels=c("1","2","3","4","5","6","7","8"))
-  data$color_available___red.factor = factor(data$color_available___red,levels=c("0","1"))
-  data$color_available___green.factor = factor(data$color_available___green,levels=c("0","1"))
-  data$color_available___blue.factor = factor(data$color_available___blue,levels=c("0","1"))
-  data$color_available___black.factor = factor(data$color_available___black,levels=c("0","1"))
-  data$motor_trend_cars_complete.factor = factor(data$motor_trend_cars_complete,levels=c("0","1","2"))
-  data$letter_group___a.factor = factor(data$letter_group___a,levels=c("0","1"))
-  data$letter_group___b.factor = factor(data$letter_group___b,levels=c("0","1"))
-  data$letter_group___c.factor = factor(data$letter_group___c,levels=c("0","1"))
-  data$choice.factor = factor(data$choice,levels=c("choice1","choice2"))
-  data$grouping_complete.factor = factor(data$grouping_complete,levels=c("0","1","2"))
-  data$color.factor = factor(data$color,levels=c("1","2","3","4"))
-  data$sale_complete.factor = factor(data$sale_complete,levels=c("0","1","2"))
+  data$redcap_repeat_instrument.factor = factor(data$redcap_repeat_instrument, levels =
+                                                  c("sale"))
+  data$cyl.factor = factor(data$cyl, levels = c("3", "4", "5", "6", "7", "8"))
+  data$vs.factor = factor(data$vs, levels = c("1", "0"))
+  data$am.factor = factor(data$am, levels = c("0", "1"))
+  data$gear.factor = factor(data$gear, levels = c("3", "4", "5"))
+  data$carb.factor = factor(data$carb, levels = c("1", "2", "3", "4", "5", "6", "7", "8"))
+  data$color_available___red.factor = factor(data$color_available___red, levels =
+                                               c("0", "1"))
+  data$color_available___green.factor = factor(data$color_available___green, levels =
+                                                 c("0", "1"))
+  data$color_available___blue.factor = factor(data$color_available___blue, levels =
+                                                c("0", "1"))
+  data$color_available___black.factor = factor(data$color_available___black, levels =
+                                                 c("0", "1"))
+  data$motor_trend_cars_complete.factor = factor(data$motor_trend_cars_complete, levels =
+                                                   c("0", "1", "2"))
+  data$letter_group___a.factor = factor(data$letter_group___a, levels =
+                                          c("0", "1"))
+  data$letter_group___b.factor = factor(data$letter_group___b, levels =
+                                          c("0", "1"))
+  data$letter_group___c.factor = factor(data$letter_group___c, levels =
+                                          c("0", "1"))
+  data$choice.factor = factor(data$choice, levels = c("choice1", "choice2"))
+  data$grouping_complete.factor = factor(data$grouping_complete, levels =
+                                           c("0", "1", "2"))
+  data$color.factor = factor(data$color, levels = c("1", "2", "3", "4"))
+  data$sale_complete.factor = factor(data$sale_complete, levels = c("0", "1", "2"))
 
-  levels(data$redcap_repeat_instrument.factor)=c("Sale")
-  levels(data$cyl.factor)=c("3","4","5","6","7","8")
-  levels(data$vs.factor)=c("Yes","No")
-  levels(data$am.factor)=c("Automatic","Manual")
-  levels(data$gear.factor)=c("3","4","5")
-  levels(data$carb.factor)=c("1","2","3","4","5","6","7","8")
-  levels(data$color_available___red.factor)=c("Unchecked","Checked")
-  levels(data$color_available___green.factor)=c("Unchecked","Checked")
-  levels(data$color_available___blue.factor)=c("Unchecked","Checked")
-  levels(data$color_available___black.factor)=c("Unchecked","Checked")
-  levels(data$motor_trend_cars_complete.factor)=c("Incomplete","Unverified","Complete")
-  levels(data$letter_group___a.factor)=c("Unchecked","Checked")
-  levels(data$letter_group___b.factor)=c("Unchecked","Checked")
-  levels(data$letter_group___c.factor)=c("Unchecked","Checked")
-  levels(data$choice.factor)=c("Choice 1","Choice 2")
-  levels(data$grouping_complete.factor)=c("Incomplete","Unverified","Complete")
-  levels(data$color.factor)=c("red","green","blue","black")
-  levels(data$sale_complete.factor)=c("Incomplete","Unverified","Complete")
+  levels(data$redcap_repeat_instrument.factor) = c("Sale")
+  levels(data$cyl.factor) = c("3", "4", "5", "6", "7", "8")
+  levels(data$vs.factor) = c("Yes", "No")
+  levels(data$am.factor) = c("Automatic", "Manual")
+  levels(data$gear.factor) = c("3", "4", "5")
+  levels(data$carb.factor) = c("1", "2", "3", "4", "5", "6", "7", "8")
+  levels(data$color_available___red.factor) = c("Unchecked", "Checked")
+  levels(data$color_available___green.factor) = c("Unchecked", "Checked")
+  levels(data$color_available___blue.factor) = c("Unchecked", "Checked")
+  levels(data$color_available___black.factor) = c("Unchecked", "Checked")
+  levels(data$motor_trend_cars_complete.factor) = c("Incomplete", "Unverified", "Complete")
+  levels(data$letter_group___a.factor) = c("Unchecked", "Checked")
+  levels(data$letter_group___b.factor) = c("Unchecked", "Checked")
+  levels(data$letter_group___c.factor) = c("Unchecked", "Checked")
+  levels(data$choice.factor) = c("Choice 1", "Choice 2")
+  levels(data$grouping_complete.factor) = c("Incomplete", "Unverified", "Complete")
+  levels(data$color.factor) = c("red", "green", "blue", "black")
+  levels(data$sale_complete.factor) = c("Incomplete", "Unverified", "Complete")
 
   data
 }
diff --git a/tests/testthat/helper-paths.R b/tests/testthat/helper-paths.R
index 19c8ff1..ff92f4a 100644
--- a/tests/testthat/helper-paths.R
+++ b/tests/testthat/helper-paths.R
@@ -6,4 +6,5 @@
 #   )
 # }
 
-get_data_location <- function(x) file.path("data", x)
+get_data_location <- function(x)
+  file.path("data", x)
diff --git a/tests/testthat/test-API.R b/tests/testthat/test-API.R
index b666859..538c2a6 100644
--- a/tests/testthat/test-API.R
+++ b/tests/testthat/test-API.R
@@ -1,26 +1,12 @@
-context("Reading in JSON")
 
 # Check the RCurl export ---------------------------------------------------
 test_that("JSON character vector from RCurl matches reference", {
+  metadata <- jsonlite::fromJSON(get_data_location("ExampleProject_metadata.json"))
 
-  metadata <- jsonlite::fromJSON(
-    get_data_location(
-      "ExampleProject_metadata.json"
-    )
-  )
-
-  records <- jsonlite::fromJSON(
-    get_data_location(
-      "ExampleProject_records.json"
-    )
-  )
+  records <- jsonlite::fromJSON(get_data_location("ExampleProject_records.json"))
 
   redcap_output_json1 <- REDCap_split(records, metadata)
 
   expect_known_hash(redcap_output_json1, "2c8b6531597182af1248f92124161e0c")
 
 })
-
-# Check the httr export ---------------------------------------------------
-
-# Something will go here.
diff --git a/tests/testthat/test-csv-exports.R b/tests/testthat/test-csv-exports.R
index f6bc83c..a028cdf 100644
--- a/tests/testthat/test-csv-exports.R
+++ b/tests/testthat/test-csv-exports.R
@@ -1,4 +1,3 @@
-context("CSV Exports")
 
 # Set up the path and data -------------------------------------------------
 metadata <- read.csv(
@@ -6,10 +5,8 @@ metadata <- read.csv(
   stringsAsFactors = TRUE
 )
 
-records <- read.csv(
-  get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
-  stringsAsFactors = TRUE
-)
+records <- read.csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
+                    stringsAsFactors = TRUE)
 
 redcap_output_csv1 <- REDCap_split(records, metadata)
 
@@ -21,48 +18,38 @@ test_that("CSV export matches reference", {
 # Test that R code enhanced CSV export matches reference --------------------
 if (requireNamespace("Hmisc", quietly = TRUE)) {
   test_that("R code enhanced export matches reference", {
-      redcap_output_csv2 <- REDCap_split(REDCap_process_csv(records), metadata)
+    redcap_output_csv2 <-
+      REDCap_split(REDCap_process_csv(records), metadata)
 
-      expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
+    expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
   })
 }
 
 
 if (requireNamespace("readr", quietly = TRUE)) {
-
   context("Compatibility with readr")
 
-  metadata <- readr::read_csv(
-    get_data_location(
-      "ExampleProject_DataDictionary_2018-06-07.csv"
-    )
-  )
+  metadata <- readr::read_csv(get_data_location("ExampleProject_DataDictionary_2018-06-07.csv"))
 
-  records <- readr::read_csv(
-    get_data_location(
-      "ExampleProject_DATA_2018-06-07_1129.csv"
-    )
-  )
+  records <- readr::read_csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"))
 
   redcap_output_readr <- REDCap_split(records, metadata)
 
   expect_matching_elements <- function(FUN) {
     FUN <- match.fun(FUN)
-    expect_identical(
-      lapply(redcap_output_readr, FUN),
-      lapply(redcap_output_csv1, FUN)
-    )
+    expect_identical(lapply(redcap_output_readr, FUN),
+                     lapply(redcap_output_csv1, FUN))
   }
 
-  test_that("Result of data read in with `readr` will match result with `read.csv`", {
+  test_that("Result of data read in with `readr` will match result with `read.csv`",
+            {
+              # The list itself
+              expect_identical(length(redcap_output_readr), length(redcap_output_csv1))
+              expect_identical(names(redcap_output_readr), names(redcap_output_csv1))
 
-    # The list itself
-    expect_identical(length(redcap_output_readr), length(redcap_output_csv1))
-    expect_identical(names(redcap_output_readr), names(redcap_output_csv1))
-
-    # Each element of the list
-    expect_matching_elements(names)
-    expect_matching_elements(dim)
-  })
+              # Each element of the list
+              expect_matching_elements(names)
+              expect_matching_elements(dim)
+            })
 
 }
diff --git a/tests/testthat/test-forms-arg.R b/tests/testthat/test-forms-arg.R
index 74c3507..0c117e5 100644
--- a/tests/testthat/test-forms-arg.R
+++ b/tests/testthat/test-forms-arg.R
@@ -1,63 +1,57 @@
-context("Using the `forms = 'all'` argument")
+
 
 # Global variables --------------------------------------------------------
 
 # Cars
-metadata <- jsonlite::fromJSON(
-  get_data_location(
-    "ExampleProject_metadata.json"
-  )
-)
+metadata <-
+  jsonlite::fromJSON(get_data_location("ExampleProject_metadata.json"))
 
-records <- jsonlite::fromJSON(
-  get_data_location(
-    "ExampleProject_records.json"
-  )
-)
+records <-
+  jsonlite::fromJSON(get_data_location("ExampleProject_records.json"))
 
 redcap_output_json <- REDCap_split(records, metadata, forms = "all")
 
 # Longitudinal
 file_paths <- sapply(
-  c(
-    records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
-    metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"
-  ), get_data_location
+  c(records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
+    metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"),
+  get_data_location
 )
 
 redcap <- lapply(file_paths, read.csv, stringsAsFactors = FALSE)
-redcap[["metadata"]] <- with(redcap, metadata[metadata[,1] > "",])
-redcap_output_long <- with(redcap, REDCap_split(records, metadata, forms = "all"))
+redcap[["metadata"]] <- with(redcap, metadata[metadata[, 1] > "",])
+redcap_output_long <-
+  with(redcap, REDCap_split(records, metadata, forms = "all"))
 redcap_long_names <- names(redcap[[1]])
 
 # Tests -------------------------------------------------------------------
 
 test_that("Each form is an element in the list", {
-
   expect_length(redcap_output_json, 3L)
-  expect_identical(names(redcap_output_json), c("motor_trend_cars", "grouping", "sale"))
+  expect_identical(names(redcap_output_json),
+                   c("motor_trend_cars", "grouping", "sale"))
 
 })
 
 test_that("All variables land somewhere", {
-
-  expect_true(setequal(names(records), Reduce("union", sapply(redcap_output_json, names))))
+  expect_true(setequal(names(records), Reduce(
+    "union", sapply(redcap_output_json, names)
+  )))
 
 })
 
 
 test_that("Primary table name is ignored", {
-  expect_identical(
-    REDCap_split(records, metadata, "HELLO", "all"),
-    redcap_output_json
-  )
+  expect_identical(REDCap_split(records, metadata, "HELLO", "all"),
+                   redcap_output_json)
 })
 
 test_that("Supports longitudinal data", {
-
   # setdiff(redcap_long_names, Reduce("union", sapply(redcap_output_long, names)))
   ##  [1] "informed_consent_and_addendum_timestamp"
 
-  expect_true(setequal(redcap_long_names, Reduce("union", sapply(redcap_output_long, names))))
+  expect_true(setequal(redcap_long_names, Reduce(
+    "union", sapply(redcap_output_long, names)
+  )))
 
 })
diff --git a/tests/testthat/test-longitudinal.R b/tests/testthat/test-longitudinal.R
index 3b955c3..95b5d87 100644
--- a/tests/testthat/test-longitudinal.R
+++ b/tests/testthat/test-longitudinal.R
@@ -1,4 +1,4 @@
-context("Longitudinal data")
+## "Longitudinal data"
 
 test_that("CSV export matches reference", {
   file_paths <- sapply(
diff --git a/tests/testthat/test-primary-table-name.R b/tests/testthat/test-primary-table-name.R
index 0c3a31b..5f7df00 100644
--- a/tests/testthat/test-primary-table-name.R
+++ b/tests/testthat/test-primary-table-name.R
@@ -1,28 +1,17 @@
-context("Primary table name processing")
+## "Primary table name processing"
 
 
 # Global  variables -------------------------------------------------------
-metadata <- jsonlite::fromJSON(
-  get_data_location(
-    "ExampleProject_metadata.json"
-  )
-)
+metadata <- jsonlite::fromJSON(get_data_location("ExampleProject_metadata.json"))
 
-records <- jsonlite::fromJSON(
-  get_data_location(
-    "ExampleProject_records.json"
-  )
-)
+records <- jsonlite::fromJSON(get_data_location("ExampleProject_records.json"))
 
 ref_hash <- "2c8b6531597182af1248f92124161e0c"
 
 # Tests -------------------------------------------------------------------
 test_that("Will not use a repeating instrument name for primary table", {
-
-  redcap_output_json1 <- expect_warning(
-    REDCap_split(records, metadata, "sale"),
-    "primary table"
-  )
+  redcap_output_json1 <- expect_warning(REDCap_split(records, metadata, "sale"),
+                                        "primary table")
 
   expect_known_hash(redcap_output_json1, ref_hash)