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src.R
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src.R
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### Statistics ########################################
get_stat<-function(data,covar,mediator,exposure,interactionterm,outcome,M=NULL,O=NULL){
# Pick only the covariates
df_cov <- data[ , covar, drop = FALSE]
# Loop over every column and get the mean
mcv<-sapply(df_cov, mean, na.rm = T)
form_M <- paste(mediator, "~", exposure, "+", paste(covar, collapse = " + "))
if(M==1){
outm.fit<-glm(as.formula(form_M), family=binomial(link=logit), data = data)
ssm<-NULL
}
if(M==0){
outm.fit<-lm(as.formula(form_M), data = data)
ssm<-(summary(outm.fit)$sigma)**2
}
bcv<-sapply(covar, function(x) coef(summary(outm.fit))[x,"Estimate"])
b0<-coef(summary(outm.fit))["(Intercept)","Estimate"]
b1<-coef(summary(outm.fit))[exposure,"Estimate"]
bcc<-sum(bcv*mcv)
#browser()
form_Y <- paste( outcome, "~", exposure, "+", mediator, "+", interactionterm, "+", paste(covar, collapse = " + "))
if(O==1){
outy.fit<-glm(as.formula(form_Y), family=binomial(link=logit), data = data)
}
if(O==0){
outy.fit<-glm(as.formula(form_Y), family=gaussian(link=identity), data = data)
}
t1<-coef(summary(outy.fit))[exposure,"Estimate"]
t2<-coef(summary(outy.fit))[mediator, "Estimate"]
t3<-coef(summary(outy.fit))[paste(exposure,mediator,sep=':'), "Estimate"]
return(c( bcc,b0,t1,t2,t3,b1,ssm ))
}
### Bootstrap ########################################
boot.bMbO<- function(data, indices)
{
outcome<- Y
exposure<- A
mediator<- M
covar<-COVAR
interactionterm<- paste(mediator,exposure,sep='*')
data<-data[indices, ]
statistics<-get_stat(data,covar,mediator,exposure,interactionterm,outcome,M=1,O=1)
bcc<-statistics[1]
b0<-statistics[2]
t1<-statistics[3]
t2<-statistics[4]
t3<-statistics[5]
b1<-statistics[6]
total<- exp(t1*a)*(1+exp(b0+b1*astar+bcc))*(1+exp(b0+b1*a+bcc+t2+t3*a)) / ( exp(t1*astar)*(1+exp(b0+b1*a+bcc))* (1+ exp(b0+b1*astar+bcc+t2+t3*astar)))
cde_comp1<- exp(t1*(a - astar) + t2*mstar + t3*a*mstar)
cde_comp2<-(1+exp(b0+b1*astar+bcc))
cde_comp3<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
cde_comp4<- exp(t2*mstar+t3*astar*mstar)
cde_comp5<-(1+exp(b0+b1*astar+bcc))
cde_comp6<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
cde_comp<- cde_comp1*cde_comp2/cde_comp3-cde_comp4*cde_comp5/cde_comp6
intref_comp1<- exp(t1*(a-astar))
intref_comp2<-(1+exp(b0+b1*astar+bcc+t2+t3*a))
intref_comp3<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
intref_comp4<- exp(t1*(a-astar)+t2*mstar+t3*a*mstar)
intref_comp5<-(1+exp(b0+b1*astar+bcc))
intref_comp6<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
intref_comp7<- exp(t2*mstar+t3*astar*mstar)
intref_comp8<-(1+exp(b0+b1*astar+bcc))
intref_comp9<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
intref_comp<-intref_comp1*intref_comp2/intref_comp3-1-intref_comp4*intref_comp5/intref_comp6 + intref_comp7*intref_comp8/intref_comp9
intmed_comp1<- exp(t1*(a-astar))
intmed_comp2<-(1+exp(b0+b1*a+bcc+t2+t3*a))
intmed_comp3<-(1+exp(b0+b1*astar+bcc))
intmed_comp4<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
intmed_comp5<-(1+exp(b0+b1*a+bcc))
intmed_comp6<-(1+exp(b0+b1*a+bcc+t2+t3*astar))
intmed_comp7<-(1+exp(b0+b1*astar+bcc))
intmed_comp8<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
intmed_comp9<-(1+exp(b0+b1*a+bcc))
intmed_comp10<- exp(t1*(a-astar))
intmed_comp11<-(1+exp(b0+b1*astar+bcc+t2+t3*a))
intmed_comp12<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
intmed_comp<- intmed_comp1*intmed_comp2*intmed_comp3/(intmed_comp4*intmed_comp5)-intmed_comp6*intmed_comp7/(intmed_comp8*intmed_comp9)-intmed_comp10*intmed_comp11/intmed_comp12 + 1
pie_comp1<-(1+exp(b0+b1*astar+bcc))
pie_comp2<-(1+exp(b0+b1*a+bcc+t2+t3*astar))
pie_comp3<-(1+exp(b0+b1*a+bcc))
pie_comp4<-(1+exp(b0+b1*astar+bcc+t2+t3*astar))
pie_comp<-(pie_comp1*pie_comp2)/(pie_comp3*pie_comp4) - 1
terr<- cde_comp + intref_comp + intmed_comp + pie_comp
excess_rr_total<- total - 1
excess_rr_cde<- cde_comp*(total - 1)/terr
excess_rr_intref<- intref_comp*(total - 1)/terr
excess_rr_intmed<- intmed_comp*(total - 1)/terr
excess_rr_pie<- pie_comp*(total - 1)/terr
prop_cde<- cde_comp/terr
prop_intmed<- intmed_comp/terr
prop_intref<- intref_comp/terr
prop_pie<- pie_comp/terr
prop_med<- (pie_comp + intmed_comp)/terr
prop_int<- (intmed_comp + intref_comp)/terr
prop_elm<- (pie_comp + intmed_comp + intref_comp)/terr
ests<- c(total, excess_rr_total, excess_rr_cde, excess_rr_intref, excess_rr_intmed, excess_rr_pie,
prop_cde, prop_intref, prop_intmed, prop_pie, prop_med, prop_int, prop_elm)
return(ests)
}
boot.cMcO<- function(data, indices)
{
data<-data[indices, ]
outcome<- Y
exposure<- A
mediator<- M
covar<-COVAR
interactionterm<- paste(mediator,exposure,sep='*')
statistics<-get_stat(data,covar,mediator,exposure,interactionterm, outcome,M=0,O=0)
bcc<-statistics[1]
b0<-statistics[2]
t1<-statistics[3]
t2<-statistics[4]
t3<-statistics[5]
b1<-statistics[6]
cde<- (t1+t3*mstar)*(a-astar)
intref<- t3*(b0+b1*astar+bcc-mstar)*(a-astar)
intmed<- t3*b1*(a-astar)*(a-astar)
pie_comp<-(t2*b1+t3*b1*astar)*(a-astar)
te<-cde+ intref + intmed + pie_comp
prop_cde<- cde/te
prop_intref<- intref/te
prop_intmed<- intmed/te
prop_pie<-pie_comp/te
prop_med<- (pie_comp + intmed)/te
prop_int<- (intmed + intref)/te
prop_elm<- (pie_comp + intmed + intref)/te
ests<- c(te, cde, intref, intmed, pie_comp, prop_cde, prop_intref, prop_intmed, prop_pie, prop_med, prop_int, prop_elm)
return(ests)
}
boot.cMbO<- function(data, indices)
{
data<-data[indices, ]
outcome<- Y
exposure<- A
mediator<- M
covar<-COVAR
interactionterm<- paste(mediator,exposure,sep='*')
statistics<-get_stat(data,covar,mediator,exposure,interactionterm, outcome,M=0,O=1)
bcc<-statistics[1]
b0<-statistics[2]
t1<-statistics[3]
t2<-statistics[4]
t3<-statistics[5]
b1<-statistics[6]
ssm<-statistics[7]
total<-exp(t1 + t2*b1 + (t3*(b0 + b1*astar + b1*a + bcc + t2*ssm)*(a - astar)) + (0.5*(t3*t3)*ssm*((a*a)-(astar*astar))))
#browser()
cde_comp1<-t1*(a - astar) + t2*mstar + t3*a*mstar
cde_comp2<-(t2 + t3*astar)*(b0 + b1*astar + bcc)
cde_comp3<-0.5*(t2 + t3*astar)*(t2 + t3*astar)*ssm
cde_comp4<-t2*mstar + t3*astar*mstar
cde_comp5<-(t2 + t3*astar)*(b0 + b1*astar + bcc)
cde_comp6<-0.5*(t2 + t3*astar)*(t2 + t3*astar)*ssm
cde_comp<-exp(cde_comp1 - cde_comp2 - cde_comp3) - exp(cde_comp4 - cde_comp5 - cde_comp6)
intref_comp1<-(t1 + t3*(b0 + b1*astar + bcc + t2*ssm)*(a - astar)) + (0.5*(t3*t3)*ssm*((a*a)-(astar*astar)))
intref_comp2<-(t1*(a - astar) + t2*mstar + t3*a*mstar) - ((t2 + t3*astar)*(b0 + b1*astar + bcc)) - (0.5*(t2 + t3*astar)*(t2 + t3*astar)*ssm)
intref_comp3<-(t2*mstar + t3*astar*mstar) - ((t2 + t3*astar)*(b0 + b1*astar + bcc)) - (0.5*(t2 + t3*astar)*(t2 + t3*astar)*ssm)
intref_comp<-exp(intref_comp1) - 1 - exp(intref_comp2) + exp(intref_comp3)
intmed_comp1<-(t1 + t2*b1 + t3*(b0 + b1*astar + b1*a + bcc + t2*ssm))*(a - astar) + (0.5*(t3*t3)*ssm*((a*a)-(astar*astar)))
intmed_comp2<-(t2*b1 + t3*b1*astar)*(a - astar)
intmed_comp3<-(t1 + t3*(b0 + b1*astar + bcc + t2*ssm))*(a - astar) + (0.5*(t3*t3)*ssm*((a*a)-(astar*astar)))
intmed_comp<-exp(intmed_comp1) - exp(intmed_comp2) - exp(intmed_comp3) + 1
pie_comp<-exp(((t2*b1 + t3*b1*astar)*(a - astar))) - 1
terr<-cde_comp + intref_comp + intmed_comp + pie_comp
excess_rr_total<-total - 1
excess_rr_cde<-cde_comp*(total - 1)/terr
excess_rr_intref<-intref_comp*(total - 1)/terr
excess_rr_intmed<-intmed_comp*(total - 1)/terr
excess_rr_pie<-pie_comp*(total - 1)/terr
prop_cde<-cde_comp/terr
prop_intref<-intref_comp/terr
prop_intmed<-intmed_comp/terr
prop_pie<-pie_comp/terr
prop_med<-(pie_comp + intmed_comp)/terr
prop_int<-(intmed_comp + intref_comp)/terr
prop_elm<-(pie_comp + intmed_comp + intref_comp)/terr
ests<- c(total, excess_rr_total, excess_rr_cde, excess_rr_intref, excess_rr_intmed, excess_rr_pie,
prop_cde, prop_intref, prop_intmed, prop_pie, prop_med, prop_int, prop_elm)
return(ests)
}
boot.bMcO <- function(data, indices)
{
data<-data[indices, ]
outcome<- Y
exposure<- A
mediator<- M
covar<-COVAR
interactionterm<- paste(mediator,exposure,sep='*')
statistics<-get_stat(data,covar,mediator,exposure,interactionterm, outcome ,M=1,O=0)
bcc<-statistics[1]
b0<-statistics[2]
t1<-statistics[3]
t2<-statistics[4]
t3<-statistics[5]
b1<-statistics[6]
cde<-(t1+t3*mstar)*(a-astar)
intref_comp1<- t3*(a-astar)
intref_comp2<- exp(b0+b1*astar+bcc)
intref_comp3<- (1+exp(b0+b1*astar+bcc))-mstar
intref<- intref_comp1*(intref_comp2/intref_comp3)
intmed_comp1<- t3*(a-astar)
intmed_comp2<- exp(b0+b1*a+bcc)
intmed_comp3<- (1+exp(b0+b1*a+bcc))
intmed_comp4<- exp(b0+b1*astar+bcc)
intmed_comp5<- (1+exp(b0+b1*astar+bcc))
intmed<- intmed_comp1*(intmed_comp2/intmed_comp3-intmed_comp4/intmed_comp5)
pie_comp1<-(t2+t3*astar)
pie_comp2<- exp(b0+b1*a+bcc)
pie_comp3<-(1+exp(b0+b1*a+bcc))
pie_comp4<- exp(b0+b1*astar+bcc)
pie_comp5<-(1+exp(b0+b1*astar+bcc))
pie_comp<- pie_comp1*(pie_comp2/pie_comp3-pie_comp4/pie_comp5)
te<- cde + intref + intmed + pie_comp
prop_cde<- cde/te
prop_intref<- intref/te
prop_intmed<- intmed/te
prop_pie<- pie_comp/te
prop_med<- (pie_comp + intmed)/te
prop_int<- (intmed + intref)/te
prop_elm<- (pie_comp + intmed + intref)/te
ests<- c(te, cde, intref, intmed, pie_comp, prop_cde, prop_intref, prop_intmed, prop_pie, prop_med, prop_int, prop_elm)
return(ests)
}
### Results ########################################
save_results<-function(boot_function=NULL,output=NULL, N=NULL){
#set a seed so that can repeat resampling and get the same results
set.seed(3000)
system.time(results<- boot(data = data, statistic = boot_function, R = N))
#collecting results so that they can be output into a single file
df_list<-list()
if (outcome==1) {
ESTIMAND<-c(
"Total Effect Risk Ratio", "Total Excess Relative Risk", "Excess Relative Risk due to CDE", "Excess Relative Risk due to INTref",
"Excess Relative Risk due to INTmed","Excess Relative Risk due to PIE", "Proportion CDE", "Proportion INTref",
"Proportion INTmed", "Proportion PIE", "Overall Proportion Mediated",
"Overall Proportion Attributable to Interaction","Overall Proportion Eliminated"
)
index=13
}
else if (outcome==0) {
ESTIMAND<-c(
"Total Effect", "CDE", "INTref", "INTmed",
"PIE","Proportion CDE","Proportion INTref",
"Proportion INTmed", "Proportion PIE", "Overall Proportion Mediated",
"Overall Proportion Attributable to Interaction","Overall Proportion Eliminated"
)
index=12
}
for (i in 1:index){
r<-boot.ci(results, type = "basic", index=i)
estq<-r[[2]]
cis<- r[[4]]
colnames(cis)<-NULL
lcl<-cis[1,4]
ucl<-cis[1,5]
estimand<-ESTIMAND[i]
rdf<-data.frame(estimand, estq, lcl, ucl)
names(rdf)<-c("Estimand", "Estimate", "LCL", "UCL")
df_list[[i]]<-rdf
}
# Putting all this together
allresults<-rbindlist(df_list)
write.csv(allresults, output)
}