# figure 3

data3 <- data %>%
rename(immunity = q8haveimmunity,
outings = Going_out_total,
noworry = q9worry,
rself = q10arisk,
rothers = q10brisk,
think_covid = Ever_covid) %>%
select(immunity,
outings,
noworry,
rself,
rothers,
think_covid) %>%
mutate(think_covid = case_when(think_covid == 1 ~ "Have COVID-19",
think_covid == 0 ~ "Have Not Had COVID-19"))

#Creating separate data sets to calculate mean and standard deviation

#Immunity
d3immune <- data3 %>%
select(immunity, think_covid) %>%
group_by(think_covid) %>%
summarise(mean(immunity),
sd(immunity)) %>%
rename(mean = 'mean(immunity)',
sd = 'sd(immunity)')

d3immune <- data.frame(lapply(d3immune,
function(x) if(is.numeric(x)) round(x,2) else x))

#d3immune$desc <- paste(d3immune$mean, d3immune$sd, sep=",")

d3immune$desc <- paste("M = ",d3immune$mean, sep="") %>%
paste(", SD = ",d3immune$sd, sep="")

d3immune <- subset(d3immune, select = -c(mean,sd))

#Outings

d3outings <- data3 %>%
select(outings, think_covid) %>%
group_by(think_covid) %>%
summarise(mean(outings),
sd(outings)) %>%
rename(mean = 'mean(outings)',
sd = 'sd(outings)')

d3outings <- data.frame(lapply(d3outings,
function(x) if(is.numeric(x)) round(x,2) else x))

d3outings$desc <- paste("M = ",d3outings$mean, sep="") %>%
paste(", SD = ",d3outings$sd, sep="")

d3outings <- subset(d3outings, select = -c(mean,sd))

#No worry

d3noworry <- data3 %>%
select(noworry, think_covid) %>%
group_by(think_covid) %>%
summarise(mean(noworry),
sd(noworry)) %>%
rename(mean = 'mean(noworry)',
sd = 'sd(noworry)')

d3noworry <- data.frame(lapply(d3noworry,
function(x) if(is.numeric(x)) round(x,2) else x))

d3noworry$desc <- paste("M = ",d3noworry$mean, sep="") %>%
paste(", SD = ",d3noworry$sd, sep="")

d3noworry <- subset(d3noworry, select = -c(mean,sd))

#Risk to self

d3rself <- data3 %>%
select(rself, think_covid) %>%
group_by(think_covid) %>%
summarise(mean(rself),
sd(rself)) %>%
rename(mean = 'mean(rself)',
sd = 'sd(rself)')

d3rself <- data.frame(lapply(d3rself,
function(x) if(is.numeric(x)) round(x,2) else x))

d3rself$desc <- paste("M = ",d3rself$mean, sep="") %>%
paste(", SD = ",d3rself$sd, sep="")

d3rself <- subset(d3rself, select = -c(mean,sd))

#Risk to others

d3rothers <- data3 %>%
select(rothers, think_covid) %>%
group_by(think_covid) %>%
summarise(mean(rothers),
sd(rothers)) %>%
rename(mean = 'mean(rothers)',
sd = 'sd(rothers)')

d3rothers <- data.frame(lapply(d3rothers,
function(x) if(is.numeric(x)) round(x,2) else x))

d3rothers$desc <- paste("M = ",d3rothers$mean, sep="") %>%
paste(", SD = ",d3rothers$sd, sep="")

d3rothers <- subset(d3rothers, select = -c(mean,sd))

#Switching the table around to have Think have not as column labels

switchI <- as.data.frame(t(as.matrix(d3immune)))
switchO <- as.data.frame(t(as.matrix(d3outings)))
switchW <- as.data.frame(t(as.matrix(d3noworry)))
switchS <- as.data.frame(t(as.matrix(d3rself)))
switchR <- as.data.frame(t(as.matrix(d3rothers)))

#turning into a table
fulllist3 <- list(switchI, switchO, switchW, switchS, switchR)
fulltable3 <- rbindlist(fulllist3, use.name = FALSE)

#cleaning up fulltable3
fulltable3 <- fulltable3[-c(1, 3, 5, 7, 9)] %>%
select(2, 1)

#roundfulltable3 <- function(fulltable3, digits=3)
#numeric_columns <- sapply(fulltable3, class) == 'numeric'
#fulltable3<- round(fulltable3[numeric_columns], digits=3)

#making new columns for levels and p characteristics

level3 <- c("1 = strongly disagree to 5 = strongly agree",
"Range = 0 to 42",
"1 = not at all worried to 5 = extremely worried",
"1 = no risk at all to 4 = major risk",
"1 = no risk at all to 4 = major risk")

pchar3 <- c("I think I have some immunity to COVID-19",
"Total out-of-home activity in the last seven days",
"Worry about COVID-19",
"Perceived risk of COVID-19 to oneself",
"Perceived risk of COVID-19 to people in the UK")

#merging new and table using cbind

fulltable3 <- cbind(pchar3, level3, fulltable3)

gtfulltable3 <- gt(fulltable3) %>%
tab_spanner(
label = "Had COVID-19",
columns = c(3:4)
) %>%
cols_label(
pchar3 = "Participant characteristics"
) %>%
cols_label(
"level3" = "Level"
) %>%
cols_label(
"2" = "Think have not had COVID-19 n = 4656"
) %>%
cols_label(
"1" = "Think have had COVID-19 n = 1493"
) %>%
tab_style(cell_text(weight = "bold"),
locations = cells_column_labels(columns = everything())) %>%
tab_style(cell_text(weight = "bold"),
locations = cells_column_spanners())