#
#
############################# Simulating Likert Data ###############################
#

################################################################################

# Items (variables or columns) are related.

n <- 1143
library(MASS)
Sigma<-matrix(c(1.0, .80, .50, .20,
                .80, 1.0, .05, .05,
                .50, .05, 1.0, .05,
                .20, .05, .05, 1.0), ncol = 4)
x <- mvrnorm(n, Sigma, mu=c(5,5,5,5))
x4 <- round(rnorm(n,5,1))
rm(Sigma)
detach("package:MASS")
id <- seq(1:n)
data.1 <- data.frame(id, round(x), x4)
names(data.1)[2:5] <- c("y", "x1", "x2", "x3")
summary(data.1)

rm(x,x4,id,n)
ls()

# If recoding is desired (i.e. true factors rather than numeric items).

library(car)
data.2 <- data.1[,2:6]
for (i in 1:5){
data.2[,i] <- recode(data.2[,i], "1 = NA; 2 = 'StronglyAgree'; 3 = 'Agree';
  4 = 'SomewhatAgree'; 5 = 'Neutral'; 6 = 'SomewhatDisagree'; 7 = 'Disagree';
  8 = 'StronglyDisagree'; 9 = NA", as.factor.result = TRUE, as.numeric.result =
  FALSE)
}
id <- seq(1:nrow(data.2))
data.2 <- data.frame(id,data.2)
summary(data.1)
summary(data.2)

detach("package:car")
detach("package:MASS")
detach("package:nnet")
detach("package:survival")
detach("package:splines")

rm(i,id)
ls()

################################################################################

# Items (variables or columns) are NOT related.

n <- 1235
z <- c(1,2,3,4)
samp.fun <- function(x, n){
  sample(x, n, replace = TRUE)
  }
data.3 <- data.frame(0)
for (i in 1:9){
  data.3[1:n,i] <- samp.fun(z,n)
  }
summary(data.3)
cor(data.3)

head(data.3)
names(data.3)[1:9] <- c("x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9")
head(data.3)

# If recoding is desired (i.e. true factors rather than numeric items).

library(car)
data.4 <- data.3
for (i in 1:9){
data.4[,i] <- recode(data.3[,i],"1 = 'StronglyAgree'; 2 = 'Agree'; 3 = 'Disagree';
         4 = 'StronglyDisagree'", as.factor.result = TRUE, as.numeric.result = FALSE)
}
summary(data.3)
summary(data.4)

detach("package:car")
detach("package:MASS")
detach("package:nnet")
detach("package:survival")
detach("package:splines")

rm(i,n,samp.fun,z)
ls()

################################################################################

cor(data.1[2:6])

mod.1 <- lm(y ~ x1 + x2 + x3 + x4, data.1)
summary(mod.1)

cor(data.3)

mod.2 <- lm(x1 ~ x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9, data.3)
summary(mod.2)

rm(mod.1,mod.2)
ls()





# End.