#Libraries used 

library(haven)
library(tidyverse)
library(ggplot2)
library(epiR)

# The following lines of code constitute the operationalisation of the
# working class

# Removing years prior to 2002

opryear <- subset(supersomstata, year > 2001)

# Removing observations where respondents do not subjectively see themselves
# as working class

oprclass <- subset(opryear, subclh < 2)

# Removing observations where respondents are not working, unemployed
# or enrolled in a labuor market program

oprocc <- subset(oprclass, lmsit < 4)

# Removing observations where respondents have a household income above
# 500,000 SEK/year

oprinc <- subset(oprocc, hinc5rel < 4)
  
#Working class party preference

oprincvoting <- subset(oprinc, cb10 < 11)
oprincvote <- table(oprincvoting$cb10, oprincvoting$year)

prop.table(oprincvote, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Left Party', 'Sweden Democrats',
                                  'Social Democrats', 'Centre Party',
                                  'Liberal Party', 'Moderate Party', 
                                  'Christian Democrats', 'Green Party'))+
  labs(title="Working class: Party preference",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions cb10

prop.table(table(oprincvoting$year, oprincvoting$cb10), 1)

#Subjective working class party preference

subpartypreferencesubset <- subset(oprclass, cb10 < 11)
subpartypreference <- table(subpartypreferencesubset$cb10, 
                            subpartypreferencesubset$year)

prop.table(subpartypreference, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Left Party', 'Sweden Democrats',
                                  'Social Democrats', 'Centre Party',
                                  'Liberal Party', 'Moderate Party', 
                                  'Christian Democrats', 'Green Party'))+
  labs(title="Subjective working class: Party preference",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions cb10

prop.table(subpartypreference, 1)

#General population party preference

genpartypreferencesubset <- subset(opryear, cb10 < 11)
genpartypreference <- table(genpartypreferencesubset$cb10,
                            genpartypreferencesubset$year)

prop.table(genpartypreference, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Left Party', 'Sweden Democrats',
                                  'Social Democrats', 'Centre Party',
                                  'Liberal Party', 'Moderate Party', 
                                  'Christian Democrats', 'Green Party'))+
  labs(title="General population: Party preference",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions cb10

prop.table(genpartypreference, 1)

#Working class trust in government

oprgovsubset <- subset(oprincvoting, aa10a < 6)
oprgov <- table(oprgovsubset$aa10a, oprgovsubset$year)

prop.table(oprgov, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -"Group") %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, color=Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
      labels = c('Very high trust', 'Quite high trust',
                   'Neither high nor low trust', 'Quite low trust',
                        'very low trust'))+
  labs(title="Working class: Trust in government",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions aa10a

prop.table(oprgov, 1)

#Subjective working class trust in government

subgovsubset <- subset(oprclass, aa10a < 6)
subgov <- table(subgovsubset$aa10a, subgovsubset$year)

prop.table(subgov, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very high trust', 'Quite high trust',
                                  'Neither high nor low trust', 'Quite low trust',
                                  'very low trust'))+
  labs(title="Subjective working class: Trust in government",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()
  

# Table of proportions aa10a

prop.table(table(subgovsubset$year, subgovsubset$aa10a),1)

#General population trust in government

gengovsubset <- subset(opryear, aa10a < 6)
gengov <- table(gengovsubset$aa10a, gengovsubset$year)

prop.table(gengov, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very high trust', 'Quite high trust',
                                  'Neither high nor low trust', 'Quite low trust',
                                  'very low trust'))+
  labs(title="General population: Trust in government",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions aa10a

prop.table(table(gengovsubset$year, gengovsubset$aa10a),1)


oprtaxsubset <- subset(oprincvoting, dc900b < 6)
oprtax <- table(oprtaxsubset$dc900b, oprtaxsubset$year)

prop.table(oprtax, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Working class: Proposal, lower taxes",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions dc900b

prop.table(table(oprtaxsubset$year,oprtaxsubset$dc900b),1)

oprpublicsubset <- subset(oprincvoting, ea900a < 6)
oprpublic <- table(oprpublicsubset$ea900a, oprpublicsubset$year)

prop.table(oprpublic, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Working class: Proposal, reduce the public sector",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions ea900a

prop.table(table(oprpublicsubset$year, oprpublicsubset$ea900a),1)

#Working class attitudes increase privatisation of healthcare

oprsjuksubset <- subset(oprincvoting, ed900a < 6)
oprsjuk <- table(oprsjuksubset$ed900a, oprsjuksubset$year)

prop.table(oprsjuk, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Working class: Proposal, increase the privatisation of healthcare",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions ed900a

prop.table(table(oprsjuksubset$year, oprsjuksubset$ed900a),1)

#Working class attitudes accept fewer refugees into Sweden

oprimsubset <- subset(oprincvoting, fc900b < 6)
oprim <- table(oprimsubset$fc900b, oprimsubset$year)

prop.table(oprim, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Working class: Proposal, accept fewer refugees into Sweden",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions fc900b

prop.table(table(oprimsubset$year, oprimsubset$fc900b),1)

#Working class trust in the daily press

oprmediatrustsubset <- subset(oprincvoting, aa10g< 6)
oprmediatrust <- table(oprmediatrustsubset$aa10g, oprmediatrustsubset$year)

prop.table(oprmediatrust, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very high trust', 'Quite high trust',
                                  'Neither high  nor low trust',
                                  'Quite low trust',
                                  'Very low trust'))+
  labs(title="Working class: Trust in the daily press",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions aa10g

prop.table(table(oprmediatrustsubset$year, oprmediatrustsubset$aa10g),1)

#Subjective working class attitudes towards lowering taxes

subtaxsubset <- subset(oprclass, dc900b < 6)
subtax <- table(subtaxsubset$dc900b, subtaxsubset$year)

prop.table(subtax, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Subjective working class: Proposal, lower taxes",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions dc900b

prop.table(table(subtaxsubset$year, subtaxsubset$dc900b),1)

#Subjective working class attitudes towards reducing the public sector

subpublicsubset <- subset(oprclass, ea900a < 6)
subpublic <- table(subpublicsubset$ea900a, subpublicsubset$year)

prop.table(subpublic, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Subjective working class: Proposal, reduce the public sector",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions ea900a

prop.table(table(subpublicsubset$year, subpublicsubset$ea900a),1)

#Subjective working class attitudes towards increasing privatisation of healthcare

subsjuksubset <- subset(oprclass, ed900a < 6)
subsjuk <- table(subsjuksubset$ed900a, subsjuksubset$year)

prop.table(subsjuk, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Subjective working class: Proposal, increase the 
       privatisation of healthcare",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions ed900a

prop.table(table(subsjuksubset$year, subsjuksubset$ed900a),1)

#Subjective working class attitudes towards accepting fewer refugees into Sweden

subimsubset <- subset(oprclass, fc900b < 6)
subim <- table(subimsubset$fc900b, subimsubset$year)

prop.table(subim, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="Subjective working class: Proposal, accept fewer refugees into Sweden",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions fc900b

prop.table(table(subimsubset$year, subimsubset$fc900b),1)

#Subjective working class trust in the daily press

submediatrustsubset <- subset(oprclass, aa10g < 6)
submedia <- table(submediatrustsubset$aa10g, submediatrustsubset$year)

prop.table(submedia, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very high trust', 'Quite high trust',
                                  'Neither high  nor low trust',
                                  'Quite high trust',
                                  'Very low trust'))+
  labs(title="Subjective working class: Trust in the daily press",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions aa10g

prop.table(table(submediatrustsubset$year, submediatrustsubset$aa10g),1)

#General population attitudes towards lowering taxation

gentaxsubset <- subset(opryear, dc900b < 6)
gentax <- table(gentaxsubset$dc900b, gentaxsubset$year)

prop.table(gentax, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="General population: Proposal, lower taxation",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions dc900b

prop.table(table(gentaxsubset$year, gentaxsubset$dc900b),1)

#General population attitudes towards reducing the public sector

genpublicsubset <- subset(opryear, ea900a < 6)
genpublic <- table(genpublicsubset$ea900a, genpublicsubset$year)

prop.table(genpublic, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="General population: Proposal, reduce the public sector",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions ea900a

prop.table(table(genpublicsubset$year, genpublicsubset$ea900a),1)

#General population attitudes towards increasing the privatisation of healthcare

gensjuksubset <- subset(opryear, ed900a < 6)
gensjuk <- table(gensjuksubset$ed900a, gensjuksubset$year)

prop.table(gensjuk, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="General population: Proposal, increase the 
       privatisation of healthcare",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions ed900a

prop.table(table(gensjuksubset$year, gensjuksubset$ed900a),1)

#General population: Proposal accept fewer refugees into Sweden

genimsubset <- subset(opryear, fc900b < 6)
genim <- table(genimsubset$fc900b, genimsubset$year)

prop.table(genim, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very good proposal', 'Rather good proposal',
                                  'Neither good  nor bad proposal',
                                  'Rather bad proposal',
                                  'Very bad proposal'))+
  labs(title="General population: Proposal accept fewer refugees into Sweden",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportionsfc900b

prop.table(table(genimsubset$year, genimsubset$fc900b),1)

#General population: Trust in the daily press

genmediatrustsubset <- subset(opryear, aa10g < 6)
genmedia <- table(genmediatrustsubset$aa10g, genmediatrustsubset$year)

prop.table(genmedia, 2) %>% as.data.frame.matrix() %>%
  rownames_to_column("Group") %>%
  gather(x, y, -Group) %>%
  mutate(x = as.Date(gsub("X", "", x), format = "%Y")) %>%
  ggplot(aes(x, y, colour = Group)) +
  geom_line(size = 0.75)+
  scale_y_continuous(labels=scales::percent) +
  scale_color_discrete(name = 'Response alternatives',
                       labels = c('Very high trust', 'Quite high trust',
                                  'Neither high  nor low trust',
                                  'Quite low trust',
                                  'Very low trust'))+
  labs(title="General population: Trust in the daily press",
       x="Years 2002-2021", y="Share of answers (%)")+
  theme_bw()

# Table of proportions aa10g

table(genmediatrustsubset$year, genmediatrustsubset$aa10g)

# Extraction of data, operationalisation of the working class and the creation
# of a binary working class variable and votes for the Sweden Democrats
#variable.

# Creating a binary variable in which being working class = 1 and
# not being working class = 2 and a binary variable for voting for
# the Sweden Democrats = 1 and not voting for the Sweden Democrats = 2

som <- supersomstata %>%
  select(year, subclh, lmsit, hinc5rel, cb10, fb10, ea900a, 
         ed900a, dc900b, fc900b, aa10a, aa10g) %>%
  filter(year > 2001) %>%
  filter(subclh < 5) %>%
  filter(lmsit < 8) %>%
  filter(hinc5rel < 6) %>%
  filter(cb10 < 11) %>%
  mutate(arbetarklass = subclh < 2 & lmsit < 4 & hinc5rel < 4,
         arbetarklass = if_else(arbetarklass == TRUE, 1, 0)) %>%
  mutate(SD = cb10 > 9,
         SD = if_else(SD == TRUE, 1, 2))

# Checking the new data frame in order to see if the new variables
# were created

view(som)

# Odds ratio calculation: being working class and voting for the 
# Sweden Democrats

TAB <- table(som$arbetarklass, som$SD)

TAB

barplot(TAB, beside=TRUE, legend=TRUE)

epi.2by2(TAB, method="cohort.count", conf.level=0.95)

TAB2 <- matrix(c(1936, 10868, 8065, 76221), nrow=2, byrow=TRUE)

TAB2

epi.2by2(TAB2, method="cohort.count", conf.level=0.95)

#chi-squared test of independence reduce the public sector

minska_offentlig_sektor <- som %>%
  filter(ea900a < 6)

table(minska_offentlig_sektor$arbetarklass, minska_offentlig_sektor$ea900a) %>%
  chisq.test()

#chi-squared test of independence increase privatization of healthcare

öka_privatisering_av_sjukvård <- som %>%
  filter(ed900a < 6)

table(öka_privatisering_av_sjukvård$arbetarklass, 
      öka_privatisering_av_sjukvård$ed900a) %>%
  chisq.test()

#chi-squared test of independence lower taxes

sänk_skatterna <- som %>%
  filter(dc900b < 6)

table(sänk_skatterna$arbetarklass, sänk_skatterna$dc900b) %>%
  chisq.test()

#chi-squared test of independence accept fewer refugees

ta_emot_färre_flyktingar <- som %>%
  filter(fc900b < 6)

table(ta_emot_färre_flyktingar$arbetarklass, 
      ta_emot_färre_flyktingar$fc900b) %>%
  chisq.test()

#chi-squared test of independence trust in daily press

tillit_till_dagspressen <- som %>%
  filter(aa10g < 6)

table(tillit_till_dagspressen$arbetarklass, 
      tillit_till_dagspressen$aa10g) %>%
  chisq.test()

#chi-squared test of independence trust in government

tillit_till_regeringen <- som %>%
  filter(aa10a < 6)

table(tillit_till_regeringen$arbetarklass, 
      tillit_till_regeringen$aa10a) %>%
  chisq.test()