testData.R

# Generates a test dataset in the directory below:
setwd("~/2-Werk/JASP/code/EJ-dataset")
rm(list = ls())
library(MASS)

# Different items are necessary to test JASP procedures


# Continuous Variables ----------------------------------------------------

# Create mvrnorm standard normal data with cor 0.68
s <- matrix(c(1,0.68,0.68,1), nrow = 2)
mvn <- mvrnorm(100,c(0,0),s)

cont <- data.frame(contNormal = rnorm(100), # Standard Normal
                   contGamma = rgamma(100,2), # Gamma Distributed
                   contBinom = rbinom(100, 1, 0.4), # Bernoulli trials
                   contExpon = exp(rnorm(100, sd = 50)), # Exponentiated normal
                   contWide = runif(100,-9e99,9e99), # Very wide interval
                   contNarrow = runif(100,-1e-99,1e-99), # Very narrow
                   contOutlier = sample(c(rnorm(95), # With outliers
                                          c(12,-23,4.5,5.7,-3.12)),100),
                   contcor1 = mvn[,1], # Multivariate normal with cor 0.68
                   contcor2 = mvn[,2])




# Factors -----------------------------------------------------------------

fac <- data.frame(facGender = factor(sample(rep(c("m", "f"), 50), replace = F)),
                  facExperim = factor(rep(c("control", "experimental"), 50)),
                  facFive = factor(rep(1:5, 20)),
                  facFifty = factor(c(1:50,1:50)),
                  facOutlier = factor(c(rep(c("f1","f2"),49), "f3", 
                                        "totallyridiculoussuperlongfactorname")))


# Debug -------------------------------------------------------------------

# For Collinearity & exact equality
col <- rbeta(100, 23, 12)
eq <- rnorm(100,10,2.5) * rgamma(100,1)

deb <- data.frame(debString = sample(letters, 100, T), # Random letter string
                  debMiss1 = sample(c(rnorm(99,10,25), NA)), # Various # Missing
                  debMiss30 = sample(c(rnorm(70,10,25), rep(NA,30))),
                  debMiss80 = sample(c(rnorm(20,10,25), rep(NA,80))),
                  debMiss99 = sample(c(rnorm(1,10,25), rep(NA,99))),
                  debBinMiss20 = sample(c(rbinom(80,1,0.6), rep(NA, 20))),
                  debNaN = rep(NaN, 100), # All NaN
                  debNaN10 = sample(c(rnorm(90,10,25), rep(NaN,10))), # 10 NaN
                  debInf = rep(Inf, 100), # All Inf values
                  debCollin1 = col, # Three multicollinear variables
                  debCollin2 = col + 2,
                  debCollin3 = col * 2,
                  debEqual1 = eq, # Two exactly equal variables
                  debEqual2 = eq,
                  debSame = rep(12.3,100)) # Exactly the same value 100 times


# Export Datasets ---------------------------------------------------------

testData1 <- cbind(cont,fac,deb)
testData2 <- testData1[1,]

write.csv(testData1, file = "testData.csv")
write.csv(testData2, file = "testDataOneRow.csv")