#install.packages("foreign")
#install.packages("weights")
#install.packages("MASS")
#install.packages("car")
#install.packages("ggplot2")
#install.packages("car")
#install.packages("mediation")
#install.packages("car")
library(mediation)
library(foreign)
library(weights)
library(MASS)
library(car)
library(ggplot2)
library(foreign)
#install.packages("gplots")
library(gplots)
#install.packages("rcompanion")
library(rcompanion)
#install.packages("DeclareDesign")
#install.packages("DesignLibrary")
library(DeclareDesign)
library(DesignLibrary) 

#install.packages("readxl")
#install.packages("dplyr")
#install.packages("foreign")
#install.packages("lavaan")
#install.packages("sjmisc")

packages = c("readxl","dplyr","foreign","lavaan","sjmisc")
package.check <- lapply(packages, FUN = function(x) {
  if (!require(x, character.only = TRUE)) {
    install.packages(x, dependencies = TRUE)
    library(x, character.only = TRUE)
  }
})


dataSEM <- read.spss("SEMdata.sav", to.data.frame=TRUE)

#### mod.flu1 ####
mod.flu1d <- '
   # Define latent variables/measurement model
   phibelief2 =~ s1a.r_2 + s1b.r_2
   morbelief2 =~ moral1a.r_2 + moral1b.r_2 + moral1c.r_2
   
   fluatt2 =~ fv21_2 + fv8a.r_2  
   fluatt3 =~ fv21_3 + fv8a.r_3 
   fluatt4 =~ fv21_4 + fv8a.r_4
   
   # Autoregressive effects
   phibelief2 ~ age_2 + female_2 + whitedummy_2 + education_2 + income.clean_2 + parent912_2 + conservative_2 +
                r1*flu.d_protestant_2 + r2*catorth_2 + r3*flu.d_mormon_2 +  
                r4*flu.d_justchrist_2 + r5*flu.d_muslim_2 + r6*flu.d_jewish_2 + r7*buddhindu_2 +
                r8*flu.d_other_2 + r9*flu.d_unitarian_2 + r10*flu.d_agnost_2 + 
                r11*flu.d_nothing_2
   morbelief2 ~ age_2 + female_2 + whitedummy_2 + education_2 + income.clean_2 + parent912_2 + conservative_2 +
                r12*flu.d_protestant_2 + r13*catorth_2 + r14*flu.d_mormon_2 +  
                r15*flu.d_justchrist_2 + r16*flu.d_muslim_2 + r17*flu.d_jewish_2 + r18*buddhindu_2 +
                r19*flu.d_other_2 + r20*flu.d_unitarian_2 + r21*flu.d_agnost_2 + 
                r22*flu.d_nothing_2
    
   fluatt2 ~ b1*phibelief2 + b2*morbelief2            
   fluatt3 ~ a1*fluatt2 
   fluatt4 ~ a2*fluatt3
   
   fluvax.r_2 ~ b3*phibelief2 + b4*morbelief2 # Comment this line for mod.flu2
   fluvax.r_3 ~ a3*fluvax.r_2
   fluvax.r_4 ~ a4*fluvax.r_3
   
   fluvax.r_3 ~ c2*fluatt2
   fluvax.r_4 ~ c3*fluatt3

   flu.encourage_flu ~ b5*phibelief2 + b6*morbelief2   
   encourageflu_t3 ~ a5*flu.encourage_flu
   encourageflu_t4 ~ a6*encourageflu_t3
   
   encourageflu_t3 ~ c4*fluatt2
   encourageflu_t4 ~ c5*fluatt3
   
   # Correlations
   phibelief2 ~~ morbelief2

   fv21_2 ~~ fv21_3
   fv21_2 ~~ fv21_4
   fv21_3 ~~ fv21_4
   
   fv8a.r_2 ~~ fv8a.r_3
   fv8a.r_2 ~~ fv8a.r_4
   fv8a.r_3 ~~ fv8a.r_4
   
   flu.encourage_flu ~~ encourageflu_t3
   flu.encourage_flu ~~ encourageflu_t4
   encourageflu_t3 ~~ encourageflu_t4
   
   flu.encourage_flu ~~ fluvax.r_2
   encourageflu_t3 ~~ fluvax.r_3
   encourageflu_t4 ~~ fluvax.r_4 

# Indirect effects
# Religious group -> philosophical beliefs -> attitudes t2
   indirect1  := r1*b1
   indirect2  := r2*b1
   indirect3  := r3*b1
   indirect4  := r4*b1
   indirect5  := r5*b1
   indirect6  := r6*b1
   indirect7  := r7*b1
   indirect8  := r8*b1
   indirect9  := r9*b1
   indirect10 := r10*b1
   indirect11 := r11*b1

# Religious group -> moral beliefs -> attitudes t2
   indirect12 := r12*b2
   indirect13 := r13*b2
   indirect14 := r14*b2
   indirect15 := r15*b2
   indirect16 := r16*b2
   indirect17 := r17*b2
   indirect18 := r18*b2
   indirect19 := r19*b2
   indirect20 := r20*b2
   indirect21 := r21*b2
   indirect22 := r22*b2

# Religious group-> philosophical beliefs -> attitudes t2 -> vax t3
   indirect23 := r1*b1*c2
   indirect24 := r2*b1*c2
   indirect25 := r3*b1*c2
   indirect26 := r4*b1*c2
   indirect27 := r5*b1*c2
   indirect28 := r6*b1*c2
   indirect29 := r7*b1*c2
   indirect30 := r8*b1*c2
   indirect31 := r9*b1*c2
   indirect32 := r10*b1*c2
   indirect33 := r11*b1*c2

# Religious group-> moral beliefs -> attitudes t2 -> vax t3
   indirect34 := r12*b2*c2
   indirect35 := r13*b2*c2
   indirect36 := r14*b2*c2
   indirect37 := r15*b2*c2
   indirect38 := r16*b2*c2
   indirect39 := r17*b2*c2
   indirect40 := r18*b2*c2
   indirect41 := r19*b2*c2
   indirect42 := r20*b2*c2
   indirect43 := r21*b2*c2
   indirect44 := r22*b2*c2

# Religious group-> philosophical beliefs -> attitudes t2 -> encourage t3
   indirect45 := r1*b1*c4
   indirect46 := r2*b1*c4
   indirect47 := r3*b1*c4
   indirect48 := r4*b1*c4
   indirect49 := r5*b1*c4
   indirect50 := r6*b1*c4
   indirect51 := r7*b1*c4
   indirect52 := r8*b1*c4
   indirect53 := r9*b1*c4
   indirect54 := r10*b1*c4
   indirect55 := r11*b1*c4

# Religious group-> moral beliefs -> attitudes t2 -> encourage t3
   indirect56 := r12*b2*c4
   indirect57 := r13*b2*c4
   indirect58 := r14*b2*c4
   indirect59 := r15*b2*c4
   indirect60 := r16*b2*c4
   indirect61 := r17*b2*c4
   indirect62 := r18*b2*c4
   indirect63 := r19*b2*c4
   indirect64 := r20*b2*c4
   indirect65 := r21*b2*c4
   indirect66 := r22*b2*c4

# Religious group-> philosophical beliefs -> attitudes t2 -> attitude t3 -> vax t4
   indirect67 := r1*b1*a1*c3
   indirect68 := r2*b1*a1*c3
   indirect69 := r3*b1*a1*c3
   indirect70 := r4*b1*a1*c3
   indirect71 := r5*b1*a1*c3
   indirect72 := r6*b1*a1*c3
   indirect73 := r7*b1*a1*c3
   indirect74 := r8*b1*a1*c3
   indirect75 := r9*b1*a1*c3
   indirect76 := r10*b1*a1*c3
   indirect77 := r11*b1*a1*c3

# Religious group-> moral beliefs -> attitudes t2 -> attitude t3 -> vax t4
   indirect78 := r12*b2*a1*c3
   indirect79 := r13*b2*a1*c3
   indirect89 := r14*b2*a1*c3
   indirect81 := r15*b2*a1*c3
   indirect82 := r16*b2*a1*c3
   indirect83 := r17*b2*a1*c3
   indirect84 := r18*b2*a1*c3
   indirect85 := r19*b2*a1*c3
   indirect86 := r20*b2*a1*c3
   indirect87 := r21*b2*a1*c3
   indirect88 := r22*b2*a1*c3

# Religious group-> philosophical beliefs -> attitudes t2 -> attitude t3 -> encourage t4
   indirect89  := r1*b1*a1*c5
   indirect90  := r2*b1*a1*c5
   indirect91  := r3*b1*a1*c5
   indirect92 := r4*b1*a1*c5
   indirect93 := r5*b1*a1*c5
   indirect94 := r6*b1*a1*c5
   indirect95 := r7*b1*a1*c5
   indirect96 := r8*b1*a1*c5
   indirect97 := r9*b1*a1*c5
   indirect98 := r10*b1*a1*c5
   indirect99 := r11*b1*a1*c5

# Religious group-> moral beliefs -> attitudes t2 -> attitude t3 -> encourage t4
   indirect100 := r12*b2*a1*c5
   indirect101 := r13*b2*a1*c5
   indirect102 := r14*b2*a1*c5
   indirect103 := r15*b2*a1*c5
   indirect104 := r16*b2*a1*c5
   indirect105 := r17*b2*a1*c5
   indirect106 := r18*b2*a1*c5
   indirect107 := r19*b2*a1*c5
   indirect108 := r20*b2*a1*c5
   indirect109 := r21*b2*a1*c5
   indirect110 := r22*b2*a1*c5
'
##############################################################

fitflu1d <-lavaan::sem(mod.flu1d,estimator="DWLS",data=dataSEM)
fitflu1d 
lavaan::summary(fitflu1d, fit.measures = T)
r1 <- lavaan::parameterEstimates(fitflu1d,standardized = TRUE);r1
lavaan::fitMeasures(fitflu1d)
endin <- ".csv"
write.csv(r1, paste0("sem_flu-indirect_",
                     tolower(format(Sys.Date(),format="%b%d")),endin),
          row.names = FALSE) 
flu_explained<-inspect(fitflu1d, 'r2')
flu_explained
write.csv((flu_explained), file= "flu_explained.csv")


#### mod.mmr1 ####
mod.mmr1 <- '
   # Define latent variables/measurement model
   phibelief2 =~ s1a.r_2 + s1b.r_2
   morbelief2 =~ moral1a.r_2 + moral1b.r_2 + moral1c.r_2
   
   mmratt2 =~ mmr10_2 + mmr8.r_2  
   mmratt3 =~ mmr10_3 + mmr8.r_3 

   # Autoregressive effects
   phibelief2 ~ age_2 + female_2 + whitedummy_2 + education_2 + income.clean_2 + parentu6_2 + conservative_2 +
                r1*flu.d_protestant_2 + r2*catorth_2 + r3*flu.d_mormon_2 + 
                r4*flu.d_justchrist_2 + r5*flu.d_muslim_2 + r6*flu.d_jewish_2 + r7*buddhindu_2 +
                r8*flu.d_other_2 + r9*flu.d_unitarian_2 + r10*flu.d_agnost_2 + 
                r11*flu.d_nothing_2
                
   morbelief2 ~ age_2 + female_2 + whitedummy_2 + education_2 + income.clean_2 + parentu6_2 + conservative_2 +
                r12*flu.d_protestant_2 + r13*catorth_2 + r14*flu.d_mormon_2 +
                r15*flu.d_justchrist_2 + r16*flu.d_muslim_2 + r17*flu.d_jewish_2 + r18*buddhindu_2 +
                r19*flu.d_other_2 + r20*flu.d_unitarian_2 + r21*flu.d_agnost_2 + 
                r22*flu.d_nothing_2
                
   mmratt2 ~ b1*phibelief2 + b2*morbelief2            
   mmratt3 ~ a1*mmratt2 

   # Correlations
   phibelief2 ~~ morbelief2

   mmr10_2 ~~ mmr10_3
   
   mmr8.r_2 ~~ mmr8.r_3

# Indirect effects
# Religious group -> philosophical beliefs -> attitudes t2
   indirect1  := r1*b1
   indirect2  := r2*b1
   indirect3  := r3*b1
   indirect4  := r4*b1
   indirect5  := r5*b1
   indirect6  := r6*b1
   indirect7  := r7*b1
   indirect8  := r8*b1
   indirect9  := r9*b1
   indirect10 := r10*b1
   indirect11 := r11*b1

# Religious group -> moral beliefs -> attitudes t2
   indirect12 := r12*b2
   indirect13 := r13*b2
   indirect14 := r14*b2
   indirect15 := r15*b2
   indirect16 := r16*b2
   indirect17 := r17*b2
   indirect18 := r18*b2
   indirect19 := r19*b2
   indirect20 := r20*b2
   indirect21 := r21*b2
   indirect22 := r22*b2
'
##############################################################
fitmmr1 <-lavaan::sem(mod.mmr1,estimator="DWLS",data=dataSEM)
lavaan::summary(fitmmr1, fit.measures = T)
r1 <- lavaan::parameterEstimates(fitmmr1,standardized = TRUE);r1
lavaan::fitMeasures(fitmmr1)
endin <- '.csv'
write.csv(r1, paste0("sem_mmr-indirect_",
                     tolower(format(Sys.Date(),format="%b%d")),endin),
          row.names = FALSE) 
mmr_explained<-inspect(fitmmr1, 'r2')
mmr_explained
write.csv((mmr_explained), file= "mmr_explained.csv")


#### mod.hpv1 ####
mod.hpv1 <- '
   # Define latent variables/measurement model
   phibelief2 =~ s1a.r_2 + s1b.r_2
   morbelief2 =~ moral1a.r_2 + moral1b.r_2 + moral1c.r_2
   
   hpvatt2 =~ hpv10_2 + hpv8.r_2  
   hpvatt3 =~ hpv10_3 + hpv8.r_3 

   # Autoregressive effects
   phibelief2 ~ age_2 + female_2 + whitedummy_2 + education_2 + income.clean_2 + parentu6_2 + conservative_2 +
                r1*flu.d_protestant_2 + r2*catorth_2 + r3*flu.d_mormon_2 + 
                r4*flu.d_justchrist_2 + r5*flu.d_muslim_2 + r6*flu.d_jewish_2 + r7*buddhindu_2 +
                r8*flu.d_other_2 + r9*flu.d_unitarian_2 + r10*flu.d_agnost_2 + 
                r11*flu.d_nothing_2
                
   morbelief2 ~ age_2 + female_2 + whitedummy_2 + education_2 + income.clean_2 + parentu6_2 + conservative_2 +
                r12*flu.d_protestant_2 + r13*catorth_2 + r14*flu.d_mormon_2 + 
                r15*flu.d_justchrist_2 + r16*flu.d_muslim_2 + r17*flu.d_jewish_2 + r18*buddhindu_2 +
                r19*flu.d_other_2 + r20*flu.d_unitarian_2 + r21*flu.d_agnost_2 + 
                r22*flu.d_nothing_2
                
   hpvatt2 ~ b1*phibelief2 + b2*morbelief2            
   hpvatt3 ~ a1*hpvatt2 

   # Correlations
   phibelief2 ~~ morbelief2

   hpv10_2 ~~ hpv10_3
   
   hpv8.r_2 ~~ hpv8.r_3

# Indirect effects
# Religious group -> philosophical beliefs -> attitudes t2
   indirect1  := r1*b1
   indirect2  := r2*b1
   indirect3  := r3*b1
   indirect4  := r4*b1
   indirect5  := r5*b1
   indirect6  := r6*b1
   indirect7  := r7*b1
   indirect8  := r8*b1
   indirect9  := r9*b1
   indirect10 := r10*b1
   indirect11 := r11*b1

# Religious group -> moral beliefs -> attitudes t2
   indirect12 := r12*b2
   indirect13 := r13*b2
   indirect14 := r14*b2
   indirect15 := r15*b2
   indirect16 := r16*b2
   indirect17 := r17*b2
   indirect18 := r18*b2
   indirect19 := r19*b2
   indirect20 := r20*b2
   indirect21 := r21*b2
   indirect22 := r22*b2
'
##############################################################
fithpv1 <-lavaan::sem(mod.hpv1,estimator="DWLS",data=dataSEM)
lavaan::summary(fithpv1, fit.measures = T)
r1 <- lavaan::parameterEstimates(fithpv1,standardized = TRUE);r1
lavaan::fitMeasures(fithpv1)
endin <- '.csv'
write.csv(r1, paste0("sem_hpv_indirect_",
                     tolower(format(Sys.Date(),format="%b%d")),endin),
          row.names = FALSE) 
hpv_explained<-inspect(fithpv1, 'r2')
hpv_explained
write.csv((hpv_explained), file= "hpv_explained.csv")



# descriptives

library(psych)
describe(dataSEM)
descriptives_all<-describe(data_descriptive)
write.csv(descriptives_all, file = "All_Descriptives.csv")

# to get correlation matrix use spss