SIMPIC Survey Analysis

This analysis relies on likert package. TODO: Find citation

if(!require("likert")) install.packages("likert")

## Loading required package: likert

## Loading required package: ggplot2

## Loading required package: xtable

library(likert)

Load the survey records

records = read.csv("data/survey2016.csv", skip=1, na.strings=99, colClasses = "factor")
records_delegates = records[records$status == 1, ]

items  <- records_delegates[, substr(names(records_delegates), 1, 1) == "X"]

levels_ = c("1", "2", "3", "4", "5")
for(i in seq_along(items)) {
    items[,i] <- factor(items[,i], levels=levels_)
}

items1 <- items[, substr(names(items), 1, 2) == "X1"]
items2 <- items[, substr(names(items), 1, 2) == "X2"]
items3 <- items[, substr(names(items), 1, 2) == "X3"]

l1 <- likert(items1)
summary(l1)

##   Item      low  neutral     high     mean        sd
## 8 X1.8 1.333333 10.66667 88.00000 4.173333 0.6652237
## 7 X1.7 0.000000 16.00000 84.00000 4.120000 0.6567734
## 5 X1.5 3.947368 15.78947 80.26316 4.013158 0.8562464
## 6 X1.6 5.333333 16.00000 78.66667 3.986667 0.8461891
## 4 X1.4 3.260870 19.56522 77.17391 4.108696 0.8314759
## 1 X1.1 5.555556 26.66667 67.77778 3.933333 0.8969361
## 3 X1.3 7.692308 27.47253 64.83516 3.857143 0.9258201
## 2 X1.2 5.376344 31.18280 63.44086 3.881720 0.9070912

plot(l1)

l2 <- likert(items2)
summary(l2)

##     Item      low   neutral     high     mean        sd
## 6   X2.6 0.000000  1.086957 98.91304 4.684783 0.4901076
## 2   X2.2 0.000000  2.197802 97.80220 4.428571 0.5404290
## 4   X2.4 0.000000  2.222222 97.77778 4.533333 0.5446368
## 7   X2.7 0.000000  3.260870 96.73913 4.706522 0.5249394
## 1   X2.1 0.000000  3.333333 96.66667 4.444444 0.5631195
## 5   X2.5 1.086957  3.260870 95.65217 4.554348 0.6177615
## 12 X2.12 1.086957  4.347826 94.56522 4.641304 0.6216165
## 8   X2.8 2.173913  3.260870 94.56522 4.630435 0.7065998
## 9   X2.9 2.173913  3.260870 94.56522 4.630435 0.7065998
## 10 X2.10 2.173913  4.347826 93.47826 4.521739 0.7334738
## 13 X2.13 1.086957  6.521739 92.39130 4.532609 0.6704285
## 3   X2.3 0.000000  7.777778 92.22222 4.422222 0.6356060
## 11 X2.11 2.173913  7.608696 90.21739 4.456522 0.7761987
## 14 X2.14 2.173913 13.043478 84.78261 4.315217 0.7834742
## 15 X2.15 1.086957 15.217391 83.69565 4.282609 0.8028259

plot(l2)

l3 <- likert(items3)
summary(l3)

##   Item low   neutral     high     mean        sd
## 5 X3.5   0  5.681818 94.31818 4.534091 0.6055085
## 4 X3.4   0  9.589041 90.41096 4.315068 0.6428390
## 1 X3.1   0 13.698630 86.30137 4.178082 0.6528243
## 6 X3.6   0 17.441860 82.55814 4.279070 0.7459879
## 3 X3.3   0 17.808219 82.19178 4.205479 0.7256971
## 2 X3.2   0 21.917808 78.08219 4.082192 0.7217537

plot(l3)