install.packages("emmeans", dependencies=TRUE)

install.packages("ggplot2", dependencies=TRUE)

install.packages("interactions")
install.packages("jtools")

library(interactions)
library(jtools)

library(emmeans)
library(ggplot2)
dat <-read.csv("R FOR INTERACTION.csv",header=TRUE)

###########Simple Slope Analysis for Efficacy x Descriptive Norm for Face Mask Wearing######################
model <- lm(BI_FM ~ RISK + EFFICACY_fm + DN_FM + IN_FM + RISK:EFFICACY_fm + RISK:DN_FM + EFFICACY_fm:DN_FM + IN_FM:DN_FM + Religion1 + Poli_Ide2_1 + ORDER_FM + BEH_FM + Income, data=dat)
summ(model)

interact_plot(model, pred = DN_FM, modx = EFFICACY_fm, modx.values = "plus-minus", x.label = "Descriptive Norms", y.label = "Behavioral Intention", legend.main = "Efficacy", johnson_neyman = FALSE)

sim_slopes(model, pred = DN_FM, modx = EFFICACY_fm, johnson_neyman = FALSE)


###########Simple Slope Analysis for Efficacy x Descriptive Norm for Handwashing######################

model1 <- lm(BI_HW ~ RISK + EFFICACY_HW + DN_HW + IN_HW + RISK:EFFICACY_HW + RISK:DN_HW + EFFICACY_HW:DN_HW + IN_HW:DN_HW + Order_stay_ever + BEH_HW, centered)
summ(model1)

interact_plot(model1, pred = DN_HW, modx = EFFICACY_HW, modx.values = "plus-minus", x.label = "Descriptive Norms", y.label = "Behavioral Intention", legend.main = "Efficacy")

sim_slopes(model1, pred = DN_HW, modx = EFFICACY_HW, johnson_neyman = FALSE)