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3_analysis.R
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3_analysis.R
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library(stringdist)
library(tidyverse)
library(irr)
library(combinat)
library(DescTools)
# https://journal.r-project.org/archive/2014-1/loo.pdf
df <- df %>%
mutate(dist_osa = stringdist::stringdist(a = incognito,
b = normal,
method = "osa"),
dist_dl = stringdist::stringdist(a = incognito,
b = normal,
method = "dl"))
# check for permutations
is_x_permutation_of_y <- function(x, y) {
tmp <- combinat::permn(unlist(strsplit(y, "")))
x %in% lapply(tmp, function(z) paste(z, collapse = ""))
}
df$is_incognito_permutation_of_normal <- NA
for (i in 1:dim(df)[1]) {
df$is_incognito_permutation_of_normal[i] <-
is_x_permutation_of_y(df$incognito[i], df$normal[i])
}
# a <- NA
# for (i in 1:dim(df)[1]) {
# a[i] <- is_x_permutation_of_y(df$normal[i], df$incognito[i])
# }
#
# table(df$is_incognito_permutation_of_normal == a) # it's symetrical as it should be
# table(a)
## visual check
# ggplot(df) +
# geom_bar(aes(x = dist_osa, fill = is_incognito_permutation_of_normal))
#
# df %>% filter(dist_osa > 0) %>%
# select(incognito, normal, dist_osa, is_incognito_permutation_of_normal) %>%
# View()
# summary(df$dist_osa)
# summary(df$dist_dl)
#
# table(df$dist_osa <= 1)
# table(df$dist_dl <= 1)
#
# table(df$dist_osa == 0)
# table(df$dist_osa < 1)
# table(df$incognito_equal_to_normal)
#
# table(df$dist_dl == 0)
# table(df$dist_dl < 1)
#
# table(df$dist_osa)
# table(df$dist_dl)
# table(df$dist_dl, df$dist_osa)
#
# df %>%
# filter(dist_osa == 4 & dist_dl == 3) %>%
# select(incognito, normal)
# export csv to check results in python
# pyxDamerauLevenshtein pkg used by DuckDuckGo
# df %>%
# select(id, incognito, normal, dist_osa, dist_dl) %>%
# write_csv("to_python.csv")
##### check done in .ipynb file
# The "osa" method form R package stringdist gave results equal
# to method implemented in damerau_levenshtein_distance
# form pyxdameraulevenshtein Python package
### tests
# kruskal.test(dist_osa ~ `Do eksperymentu trzeba przygotować aparaturę. Czy potrafisz włączyć tryb prywatny (incognito) w swojej przeglądarce internetowej?`,
# data = df)
# kruskal.test(dist_osa ~ `Rodzaj studiów`, data = df)
wilcox.test(dist_osa ~ `Rodzaj studiów`,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
# kruskal.test(dist_osa ~ `Twoja płeć`, data = df)
# kruskal.test(dist_osa ~ `Twój rok urodzenia`, data = df)
# # all not significant
#
#
#### compute indexes
## conservative -- liberal as 'światopogląd' (worldview) https://cbos.pl/SPISKOM.POL/2015/K_085_15.PDF
# 2nd question has reversed wording (use "8 -" shortcut)
# cons_lib_index higher == more conservative
# cor(df[,20:22]) %>% View()
df$cons_lib_index <- df[[20]] + (8 - df[[21]]) + df[[22]]
## Internet users' information privacy concerns: 'control' https://pubsonline.informs.org/doi/abs/10.1287/isre.1040.0032
# 3rd has reversed wording
# privacy_index higher == higher control
# cor(df[,27:29]) %>% View()
df$privacy_index <- df[[27]] + df[[28]] + (8 - df[[29]])
ggplot(df) +
geom_point(aes(x = cons_lib_index, y = privacy_index,
colour = ordered(dist_osa)),
size = 7, position = 'jitter', alpha = 3/4)
ggplot(df %>% filter(dist_osa > -1)) +
geom_point(aes(x = cons_lib_index, y = privacy_index,
colour = ordered(dist_osa),
shape = is_incognito_permutation_of_normal),
size = 7, position = 'jitter', alpha = 3/4)
summary(df$cons_lib_index)
summary(df$privacy_index)
DescTools::JonckheereTerpstraTest(x = df$cons_lib_index,
g = ordered(df$dist_osa),
alternative = c("decreasing"))
DescTools::JonckheereTerpstraTest(x = df$privacy_index,
g = ordered(df$dist_osa),
alternative = "increasing")
DescTools::JonckheereTerpstraTest(x = df$cons_lib_index,
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df$privacy_index,
g = ordered(df$dist_osa),
alternative = "two.sided",
nperm = 10000)
lm(formula = is_incognito_permutation_of_normal ~ privacy_index + cons_lib_index + `Rodzaj studiów` +
`Twój rok urodzenia` + `Twoja płeć`,
data = df) %>% summary()
# plot(df[[22]], df$dist_osa)
DescTools::JonckheereTerpstraTest(x = df$`Konkordat:`,
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df$`Przerywanie ciąży:`,
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df$`Związki osób tej samej płci:`,
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df[[27]],
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df[[28]],
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df[[29]],
g = ordered(df$dist_osa),
alternative = c("two.sided"))
DescTools::JonckheereTerpstraTest(x = df$`Konkordat:`,
g = ordered(df$dist_osa),
alternative = c("decreasing"))
DescTools::JonckheereTerpstraTest(x = df$`Przerywanie ciąży:`,
g = ordered(df$dist_osa),
alternative = c("decreasing"))
DescTools::JonckheereTerpstraTest(x = df$`Związki osób tej samej płci:`,
g = ordered(df$dist_osa),
alternative = c("decreasing"))
DescTools::JonckheereTerpstraTest(x = df[[27]],
g = ordered(df$dist_osa),
alternative = c("decreasing"))
DescTools::JonckheereTerpstraTest(x = df[[28]],
g = ordered(df$dist_osa),
alternative = c("decreasing"))
DescTools::JonckheereTerpstraTest(x = df[[29]],
g = ordered(df$dist_osa),
alternative = c("decreasing"))
ggplot(df) + geom_jitter(aes(x = `Przerywanie ciąży:`, y = dist_osa))
kruskal.test(cons_lib_index ~ dist_osa, data = df)
kruskal.test(privacy_index ~ dist_osa, data = df)
ggplot(df, aes(x = cons_lib_index, y = dist_osa)) + geom_point() +
geom_smooth()
ggplot(df, aes(x = privacy_index, y = dist_osa)) + geom_point() +
geom_smooth()
ggplot(df, aes(x = ordered(dist_osa), y = privacy_index)) + geom_boxplot() + geom_point()
ggplot(df, aes(x = ordered(dist_osa), y = cons_lib_index)) + geom_boxplot() + geom_point()
ggplot(df, aes(x = is_incognito_permutation_of_normal, y = cons_lib_index)) + geom_boxplot() + geom_point()
ggplot(df, aes(x = is_incognito_permutation_of_normal, y = privacy_index)) + geom_boxplot() + geom_point()
ggplot(df, aes(fill = is_incognito_permutation_of_normal, x = privacy_index)) + geom_bar()
ggplot(df, aes(fill = is_incognito_permutation_of_normal, x = cons_lib_index)) + geom_bar()
kruskal.test(privacy_index ~ is_incognito_permutation_of_normal, df)
kruskal.test(cons_lib_index ~ is_incognito_permutation_of_normal, df)
lm(dist_osa ~ privacy_index, df) %>% summary()
lm(privacy_index ~ dist_osa, df) %>% summary()
lm(privacy_index ~ cons_lib_index, df) %>% summary()
glm(is_incognito_permutation_of_normal ~
cons_lib_index + privacy_index + `Rodzaj studiów` +
`Do eksperymentu trzeba przygotować aparaturę. Czy potrafisz włączyć tryb prywatny (incognito) w swojej przeglądarce internetowej?`,
family=binomial(link = 'logit'), data = df) %>% summary()
ggplot(df, aes(x = is_incognito_permutation_of_normal,
fill = `Rodzaj studiów`)) + geom_bar( position = "fill")
chisq.test(df$is_incognito_permutation_of_normal,
df$`Rodzaj studiów`,
correct = FALSE)
wilcox.test(privacy_index ~ is_incognito_permutation_of_normal,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
wilcox.test(cons_lib_index ~ is_incognito_permutation_of_normal,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
wilcox.test(dist_osa ~ is_incognito_permutation_of_normal,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
ggplot(df, aes(x = is_incognito_permutation_of_normal, y = dist_osa)) + geom_boxplot() + geom_point()
table(df$dist_osa, df$is_incognito_permutation_of_normal)
table(df$`Twój rok urodzenia`, df$is_incognito_permutation_of_normal)
## new feature: normal_count
normal_count <- df %>% group_by(normal) %>% count() %>% rename(normal_count = "n")
df <- left_join(x = df, y = normal_count, by = 'normal')
ggplot(df, aes(x = normal_count, y = dist_osa)) + geom_point()
ggplot(df, aes(x = normal_count)) + geom_bar(aes(fill = ordered(dist_osa)))
ggplot(df, aes(x = normal_count > 1)) + geom_bar(aes(fill = ordered(dist_osa)))
wilcox.test(dist_osa ~ normal_count > 2,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
ggplot(df, aes(x = normal_count > 1)) + geom_bar(aes(fill = is_incognito_permutation_of_normal))
chisq.test(df$is_incognito_permutation_of_normal,
df$normal_count > 1,
correct = FALSE)
chisq.test(df$dist_osa > 1,
df$normal_count > 2,
correct = FALSE)
table(df$dist_osa > 1, df$normal_count > 2)
ggplot(df, aes(x = normal_count)) + geom_bar(aes(fill = is_incognito_permutation_of_normal))
ggplot(df) + geom_bar(aes(x = dist_osa, fill = normal_count > 2))
ggplot(df, aes(x = normal_count > 2, y = dist_osa)) + geom_dotplot(binaxis = "y", stackdir = "center")
ggplot(df) + geom_bar(aes(x = normal_count > 2, fill = ordered(dist_osa)))
w <- wilcox.test(dist_osa ~ normal_count > 2,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
print(w)
# Field, A., Miles, J., & Field, Z. (2012).
# Discovering Statistics Using R. SAGE Publications Ltd. pg. 665
rFromWilcox<-function(wilcoxModel, N){
z<- qnorm(wilcoxModel$p.value/2)
r<- z/ sqrt(N)
cat(wilcoxModel$data.name, 'Effect Size, r = ', r)
}
rFromWilcox(w, dim(df)[1])
wilcox.test(cons_lib_index ~ normal_count > 2,
data = df, paired=FALSE, exact=FALSE, conf.int=TRUE)
ggplot(df, aes(x = normal_count > 2, y = dist_osa)) +
geom_boxplot() +
geom_dotplot(binaxis = "y", stackdir = "center")
## new feature: incognito_count
incognito_count <- df %>% group_by(incognito) %>% count() %>% rename(incognito_count = "n")
df <- left_join(x = df, y = incognito_count, by = 'incognito')
ggplot(df) + geom_bar(aes(x = ordered(normal_count), fill = ordered(incognito_count)))
ggplot(df) + geom_bar(aes(x = ordered(normal_count > 2), fill = ordered(incognito_count)))
ggplot(df) + geom_count(aes(x = normal_count, y = incognito_count))
lm(normal_count ~ incognito_count, data = df) %>% summary()
cor.test(df$normal_count, df$incognito_count, method = "spearman")
### check time
summary(df$`Sygnatura czasowa`)
df$month_day <- paste(lubridate::month(df$`Sygnatura czasowa`), lubridate::day(df$`Sygnatura czasowa`), sep = "_")
df$month <- lubridate::month(df$`Sygnatura czasowa`)
kruskal.test(dist_osa ~ month_day, df)
kruskal.test(dist_osa ~ month, df)
wilcox.test(dist_osa ~ month,
data = df, paired = FALSE, exact = FALSE, conf.int = TRUE)
# # export final df to later use
# write_csv(df, "df_final.csv")
#
# write_csv((df_long_clean %>%
# filter(id %in% df$id)),
# "df_long_final.csv")