From 3a4cb8ee826a08de8d90bbfc3a27f5a532764fa3 Mon Sep 17 00:00:00 2001
From: JTPetter <61797391+JTPetter@users.noreply.github.com>
Date: Fri, 11 Oct 2024 16:46:39 +0200
Subject: [PATCH] Attributes chart and type 1 study data loading

---
 R/attributesCharts.R                          |  6 --
 R/doeAnalysis.R                               | 10 +--
 R/msaType1Gauge.R                             |  4 +-
 inst/Description.qml                          |  1 +
 tests/testthat/SPC_P.csv                      | 21 ------
 .../{ => datasets/attributeCharts}/SPC_NP.csv |  0
 .../datasets/attributeCharts/SPC_P.csv        | 21 ++++++
 tests/testthat/test-attributesCharts.R        | 15 ++--
 tests/testthat/test-doeAnalysis.R             | 68 +++++++++++++++++++
 tests/testthat/test-msaType1Gauge.R           |  5 ++
 10 files changed, 110 insertions(+), 41 deletions(-)
 delete mode 100644 tests/testthat/SPC_P.csv
 rename tests/testthat/{ => datasets/attributeCharts}/SPC_NP.csv (100%)
 create mode 100644 tests/testthat/datasets/attributeCharts/SPC_P.csv

diff --git a/R/attributesCharts.R b/R/attributesCharts.R
index a306c785..db99cc8d 100644
--- a/R/attributesCharts.R
+++ b/R/attributesCharts.R
@@ -23,16 +23,10 @@ attributesCharts <- function(jaspResults, dataset, options) {
   D <- options[["defectiveOrDefect"]]
   timeStamp <- options$timeStamp
 
-  numeric_variables <- c(total, D)
-  numeric_variables  <- numeric_variables[numeric_variables != ""]
-
   # Data reading
-  if (is.null(dataset))
     if (!identical(timeStamp, "")) {
-      dataset <- .readDataSetToEnd(columns.as.numeric = numeric_variables, columns.as.factor = timeStamp)
       xLabs <- as.vector(dataset[, timeStamp])
     } else {
-      dataset <- .readDataSetToEnd(columns.as.numeric = numeric_variables)
       xLabs <- NULL
     }
 
diff --git a/R/doeAnalysis.R b/R/doeAnalysis.R
index 13f1b7c3..cafc4366 100644
--- a/R/doeAnalysis.R
+++ b/R/doeAnalysis.R
@@ -36,9 +36,12 @@ doeAnalysis <- function(jaspResults, dataset, options, ...) {
     dependent <- options[["dependentResponseSurface"]]
   }
 
-  dataset <- .doeAnalysisReadData(dataset, options, continuousPredictors, discretePredictors, blocks, covariates, dependent)
+  dataset <- na.omit(dataset)
+
+  if (length(blocks) > 0 && !identical(blocks, "")) # name of variable should always be "Block"
+    names(dataset)[names(dataset) == blocks] <- "Block"
 
-  if (length(blocks) > 0 && !identical(blocks, "")) # data reading function renames the block variable to "block"
+  if (length(blocks) > 0 && !identical(blocks, ""))
     blocks <- "Block"
 
   .doeAnalysisCheckErrors(dataset, options, continuousPredictors, discretePredictors, blocks, covariates, dependent, ready)
@@ -95,8 +98,7 @@ doeAnalysis <- function(jaspResults, dataset, options, ...) {
   dataset <- .readDataSetToEnd(columns.as.numeric = numericVars, columns.as.factor = factorVars)
   dataset <- na.omit(dataset)
 
-  if (length(blocks) > 0 && !identical(blocks, "")) # name of variable should always be "Block"
-    names(dataset)[names(dataset) == blocks] <- "Block"
+
   return(dataset)
 }
 
diff --git a/R/msaType1Gauge.R b/R/msaType1Gauge.R
index b01604bd..1e0590c0 100644
--- a/R/msaType1Gauge.R
+++ b/R/msaType1Gauge.R
@@ -23,9 +23,7 @@ msaType1Gauge <- function(jaspResults, dataset, options, ...) {
 
   ready <- (length(measurements) != 0)
 
-  if (is.null(dataset)) {
-    dataset         <- .readDataSetToEnd(columns.as.numeric  = measurements, exclude.na.listwise = measurements)
-  }
+  dataset <- jaspBase::excludeNaListwise(dataset, columns = measurements)
 
   # Bias Run Chart
   if (options[["runChart"]]) {
diff --git a/inst/Description.qml b/inst/Description.qml
index 7babc83f..e4a64110 100644
--- a/inst/Description.qml
+++ b/inst/Description.qml
@@ -12,6 +12,7 @@ Description
 	website:			"https://github.com/jasp-stats/jaspQualityControl"
 	license:			"GPL (>= 2)"
 	icon:				"qualityControl-module.svg"
+	preloadData:		true
 
 	GroupTitle
 	{
diff --git a/tests/testthat/SPC_P.csv b/tests/testthat/SPC_P.csv
deleted file mode 100644
index 781cdc0b..00000000
--- a/tests/testthat/SPC_P.csv
+++ /dev/null
@@ -1,21 +0,0 @@
-"","ï..Month","Size","D","Proportion"
-"1","Sep",150,21,0.14
-"2","Oct",153,16,0.105
-"3","Nov",170,30,0.176
-"4","Dec",226,31,0.137
-"5","Jan",154,24,0.156
-"6","Feb",130,33,0.254
-"7","Mar",190,32,0.168
-"8","Apr",165,29,0.176
-"9","May",176,23,0.131
-"10","Jun",144,17,0.118
-"11","Jul",132,14,0.106
-"12","Aug",144,31,0.215
-"13","Sep",156,29,0.186
-"14","Oct",158,25,0.158
-"15","Nov",142,15,0.106
-"16","Dec",212,43,0.203
-"17","Jan",155,20,0.129
-"18","Feb",138,26,0.188
-"19","Mar",141,23,0.163
-"20","Apr",130,28,0.215
diff --git a/tests/testthat/SPC_NP.csv b/tests/testthat/datasets/attributeCharts/SPC_NP.csv
similarity index 100%
rename from tests/testthat/SPC_NP.csv
rename to tests/testthat/datasets/attributeCharts/SPC_NP.csv
diff --git a/tests/testthat/datasets/attributeCharts/SPC_P.csv b/tests/testthat/datasets/attributeCharts/SPC_P.csv
new file mode 100644
index 00000000..6f365a8e
--- /dev/null
+++ b/tests/testthat/datasets/attributeCharts/SPC_P.csv
@@ -0,0 +1,21 @@
+,Month,Size,D,Proportion
+1,Sep,150,21,0.14
+2,Oct,153,16,0.105
+3,Nov,170,30,0.176
+4,Dec,226,31,0.137
+5,Jan,154,24,0.156
+6,Feb,130,33,0.254
+7,Mar,190,32,0.168
+8,Apr,165,29,0.176
+9,May,176,23,0.131
+10,Jun,144,17,0.118
+11,Jul,132,14,0.106
+12,Aug,144,31,0.215
+13,Sep,156,29,0.186
+14,Oct,158,25,0.158
+15,Nov,142,15,0.106
+16,Dec,212,43,0.203
+17,Jan,155,20,0.129
+18,Feb,138,26,0.188
+19,Mar,141,23,0.163
+20,Apr,130,28,0.215
diff --git a/tests/testthat/test-attributesCharts.R b/tests/testthat/test-attributesCharts.R
index dbdb499b..fbc0d424 100644
--- a/tests/testthat/test-attributesCharts.R
+++ b/tests/testthat/test-attributesCharts.R
@@ -4,11 +4,12 @@ context("[Quality Control] Attributes Charts")
 # NP
 options <- analysisOptions("attributesCharts")
 options$defectiveOrDefect <- "D"
+options$defectiveOrDefect.types <- "scale"
 options$total <- "Size"
 options$attributesChart <- "defectives"
 options$attributesChartDefectivesChartType <- "npChart"
 set.seed(1)
-results <- runAnalysis("attributesCharts", "SPC_NP.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_NP.csv", options)
 
 test_that("np Chart plot matches", {
   plotName <- results[["results"]][["NPchartPlot"]][["data"]]
@@ -25,7 +26,7 @@ test_that("Test results for np chart table results match", {
 
 # P
 options$attributesChartDefectivesChartType <- "pChart"
-results <- runAnalysis("attributesCharts", "SPC_P.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_P.csv", options)
 
 test_that("p Chart plot matches", {
   plotName <- results[["results"]][["PchartPlot"]][["data"]]
@@ -35,7 +36,7 @@ test_that("p Chart plot matches", {
 
 # Laney's P
 options$attributesChartDefectivesChartType <- "laneyPPrimeChart"
-results <- runAnalysis("attributesCharts", "SPC_P.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_P.csv", options)
 
 test_that("Laney p' Chart plot matches", {
   plotName <- results[["results"]][["LaneyPPlot"]][["data"]]
@@ -48,7 +49,7 @@ test_that("Laney p' Chart plot matches", {
 options$attributesChartDefectivesChartType <- "npChart"
 options$attributesChart <- "defects"
 options$attributesChartDefectsChartType <- "cChart"
-results <- runAnalysis("attributesCharts", "SPC_NP.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_NP.csv", options)
 
 test_that("c Chart plot matches", {
   plotName <- results[["results"]][["CchartPlot"]][["data"]]
@@ -64,7 +65,7 @@ test_that("Test results for c chart table results match", {
 
 # U
 options$attributesChartDefectsChartType <- "uChart"
-results <- runAnalysis("attributesCharts", "SPC_P.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_P.csv", options)
 
 test_that("u Chart plot matches", {
   plotName <- results[["results"]][["UchartPlot"]][["data"]]
@@ -74,7 +75,7 @@ test_that("u Chart plot matches", {
 
 # Laneys U
 options$attributesChartDefectsChartType <- "laneyUPrimeChart"
-results <- runAnalysis("attributesCharts", "SPC_P.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_P.csv", options)
 
 test_that("Laney u' Chart plot matches", {
   plotName <- results[["results"]][["LaneyUPlot"]][["data"]]
@@ -84,7 +85,7 @@ test_that("Laney u' Chart plot matches", {
 
 ## I MR
 options$attributesChart <- "xmr"
-results <- runAnalysis("attributesCharts", "SPC_P.csv", options)
+results <- runAnalysis("attributesCharts", "datasets/attributeCharts/SPC_P.csv", options)
 
 test_that("Individuals and Moving Range Chart plot matches", {
   plotName <- results[["results"]][["IPlotA"]][["data"]]
diff --git a/tests/testthat/test-doeAnalysis.R b/tests/testthat/test-doeAnalysis.R
index 2fd1cd41..7c9bec22 100644
--- a/tests/testthat/test-doeAnalysis.R
+++ b/tests/testthat/test-doeAnalysis.R
@@ -10,6 +10,8 @@ context("[Quality Control] DoE Analysis")
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -64,6 +66,8 @@ test_that("1.4 Two factors full factorial Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D", "E")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -175,6 +179,9 @@ options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D", "E")
 options$covariates <- "Covariate"
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
+options$covariates.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -292,6 +299,8 @@ test_that("3.4 Five factors full factorial with covariates Model Summary table r
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D", "E")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -367,6 +376,8 @@ test_that("4.4 Five factors fractional factorial Model Summary table results mat
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D", "E", "F", "G", "H", "J")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -606,6 +617,8 @@ test_that("5.4 Nine factors highest factorial Model Summary table results match"
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D", "E", "F", "G", "H", "J")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -727,6 +740,8 @@ test_that("6.4 Nine factors smallest fractional Model Summary table results matc
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$continuousFactorsFactorial <- c("A", "B", "C")
+options$dependentFactorial.types <- "scale"
+options$continuousFactorsFactorial.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -804,6 +819,8 @@ test_that("7.4 One center point Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$continuousFactorsFactorial <- c("A", "B", "C")
+options$dependentFactorial.types <- "scale"
+options$continuousFactorsFactorial.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -880,6 +897,8 @@ test_that("8.4 Two center points Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$continuousFactorsFactorial <- c("A", "B", "C")
+options$dependentFactorial.types <- "scale"
+options$continuousFactorsFactorial.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -957,6 +976,9 @@ options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$continuousFactorsFactorial <- c("A", "B", "C")
 options$blocksFactorial <- "Blocks"
+options$dependentFactorial.types <- "scale"
+options$continuousFactorsFactorial.types <- "scale"
+options$blocksFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1076,6 +1098,8 @@ test_that("10.4 Two blocks Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("AHTC", "B")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1130,6 +1154,8 @@ test_that("13.4 Two factor one HTC Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("AHTC", "BHTC", "C", "D", "E")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1241,6 +1267,8 @@ test_that("14.4 Five factor two HTC Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("AHTC", "BHTC", "CHTC", "D", "E", "F", "G")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1406,6 +1434,8 @@ test_that("15.4 Seven factor three HTC Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- FALSE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1504,6 +1534,8 @@ test_that("16.5 Three factors three levelsModel Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- FALSE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1614,6 +1646,8 @@ test_that("17.5 Three factors 2*three and 1*four levels Model Summary table resu
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- FALSE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -1832,6 +1866,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -1914,6 +1950,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D", "E")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2034,6 +2072,9 @@ options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C")
 options$fixedFactorsResponseSurface <- c("D", "E")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
+options$fixedFactorsResponseSurface.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2147,6 +2188,9 @@ options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D")
 options$fixedFactorsResponseSurface <- c("E")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
+options$fixedFactorsResponseSurface.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2262,6 +2306,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2341,6 +2387,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2439,6 +2487,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D", "E")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2556,6 +2606,9 @@ options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D", "E", "F")
 options$fixedFactorsResponseSurface <- c("G")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
+options$fixedFactorsResponseSurface.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2722,6 +2775,8 @@ test_that("26.4 Six continuous predictors one discrete predictor BBD Model Summa
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C", "D", "E")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -2876,6 +2931,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D", "E")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -2962,6 +3019,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D", "E")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -3050,6 +3109,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -3129,6 +3190,8 @@ options <- analysisOptions("doeAnalysis")
 options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B", "C", "D")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
 options$codeFactors <- TRUE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
@@ -3206,6 +3269,8 @@ test_that("31.4 Uncoded Squared Terms Model Summary table results match", {
 options <- analysisOptions("doeAnalysis")
 options$dependentFactorial <- "Result"
 options$fixedFactorsFactorial <- c("A", "B", "C")
+options$dependentFactorial.types <- "scale"
+options$fixedFactorsFactorial.types <- "nominal"
 options$codeFactors <- FALSE
 options$codeFactorsMethod <- "automatic"
 options$tableEquation <- TRUE
@@ -3284,6 +3349,9 @@ options$designType <- "responseSurfaceDesign"
 options$dependentResponseSurface <- "Result"
 options$continuousFactorsResponseSurface <- c("A", "B")
 options$fixedFactorsResponseSurface <- c("C", "D")
+options$dependentResponseSurface.types <- "scale"
+options$continuousFactorsResponseSurface.types <- "scale"
+options$fixedFactorsResponseSurface.types <- "nominal"
 options$codeFactors <- FALSE
 options$codeFactorsMethod <- "manual"
 options$codeFactorsManualTable <- list(
diff --git a/tests/testthat/test-msaType1Gauge.R b/tests/testthat/test-msaType1Gauge.R
index b2aa2de6..8bc6eaf6 100644
--- a/tests/testthat/test-msaType1Gauge.R
+++ b/tests/testthat/test-msaType1Gauge.R
@@ -8,6 +8,7 @@ set.seed(1)
 
 options <- analysisOptions("msaType1Gauge")
 options$measurement <- "dm"
+options$measurement.types <- "scale"
 options$referenceValue <- -4
 options$toleranceRange <- 15
 options$histogram <- TRUE
@@ -51,6 +52,7 @@ test_that("1.5 Standard settings - t-test of observed bias against 0 table resul
 
 options <- analysisOptions("msaType1Gauge")
 options$measurement <- "dm"
+options$measurement.types <- "scale"
 options$referenceValue <- -4
 options$toleranceRange <- 15
 options$histogram <- TRUE
@@ -97,6 +99,7 @@ test_that("2.5 Alternative settings - t-test of observed bias against 0 table re
 
 options <- analysisOptions("msaType1Gauge")
 options$measurement <- "dmMissing1"
+options$measurement.types <- "scale"
 options$referenceValue <- -4
 options$toleranceRange <- 15
 options$histogram <- TRUE
@@ -140,6 +143,7 @@ test_that("3.5 Missing 1 value - t-test of observed bias against 0 table results
 
 options <- analysisOptions("msaType1Gauge")
 options$measurement <- "dmMissing25"
+options$measurement.types <- "scale"
 options$referenceValue <- -4
 options$toleranceRange <- 15
 options$histogram <- TRUE
@@ -183,6 +187,7 @@ test_that("4.5 Missing half values - t-test of observed bias against 0 table res
 
 options <- analysisOptions("msaType1Gauge")
 options$measurement <- "dmMissing49"
+options$measurement.types <- "scale"
 options$referenceValue <- -4
 options$toleranceRange <- 15
 options$histogram <- TRUE