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Meta-analysis/R_code_Pu.R
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## Meta_final_code | |
## by Pu | |
## 2024May2 | |
library(metafor) | |
library(readxl) | |
metafin<-read_xlsx('C:/Users/cp/Desktop/Meta Analysis/Dataset_Pu.xlsx') | |
## z adjustment | |
metafin<-escalc("ZCOR",ri=ri, ni=ni,data=metafin,var.names = c('yzi','vzi')) | |
## zero effect size | |
randem_zero<- rma(yzi,vzi, data= metafin, slab = author) | |
randem_zero | |
predict(randem_zero, digits=3, transf = transf.ztor) | |
confint(randem_zero) | |
## funnel plot | |
funnel(randem_zero) | |
## forest plot | |
forest(randem_zero, xlim = c(-1.2,1.2),atransf=transf.ztor, | |
digits = c(2,1), | |
cex=.6) | |
text(-1.2,24,"Authors(year)",pos=4, cex=1) | |
text(1.2,24,'r[95% CI]',pos=2,cex=1) | |
## small study effect test | |
regtest(randem_zero) | |
## influential case test | |
inf<- influence(randem_zero) | |
print(inf) | |
plot(inf) | |
## contour funnel plot | |
metafor::funnel(randem_zero, level=c(90, 95, 99), shade=c("white", "gray55", "gray75"), refline=0, | |
xlab= "r",legend=TRUE) | |
## number of authors | |
summary(metafin$nauthor) | |
sd(metafin$nauthor) | |
metafin$nau4<-0 | |
metafin$nau4[metafin$nauthor>=4]<-1 | |
table(metafin$nau4) | |
randem_nau4<- rma(yzi,vzi, mods= ~nau4,data= metafin, slab = author) | |
randem_nau4 | |
## moving constant | |
metafin$invernau4<-1-metafin$nau4 | |
randem_invernau4<- rma(yzi,vzi, mods= ~invernau4,data= metafin, slab = author) | |
randem_invernau4 | |
## cite | |
summary(metafin$cite) | |
sd(metafin$cite) | |
randem_cite<-rma(yzi,vzi, mods= ~cite,data= metafin, slab = author) | |
randem_cite | |
## survey length | |
summary(metafin$days) | |
sd(metafin$days,na.rm=TRUE) | |
randem_days<-rma(yzi,vzi, mods= ~days,data= metafin, slab = author) | |
randem_days | |
metafin$tw<-NA | |
metafin$tw[metafin$days>=14]<-1 | |
metafin$tw[metafin$days<14& metafin$days>0]<-0 | |
summary(metafin$tw) | |
## interpolation | |
metafin$twitpl<-1 | |
metafin$twitpl[metafin$days<14& metafin$days>0]<-0 | |
randem_tw<-rma(yzi,vzi, mods= ~tw,data= metafin, slab = author) | |
randem_tw | |
randem_twitpl<-rma(yzi,vzi, mods= ~twitpl,data= metafin, slab = author) | |
randem_twitpl | |
## moving constant | |
metafin$invertwitpl<-1-metafin$twitpl | |
randem_invertwitpl<-rma(yzi,vzi, mods= ~invertwitpl,data= metafin, slab = author) | |
randem_invertwitpl | |
## nationwide | |
metafin$nw<-0 | |
metafin$nw[metafin$scale=="nationwide"]<-1 | |
summary(metafin$nw) | |
sd(metafin$nw) | |
randem_nw<-rma(yzi,vzi, mods= ~nw,data= metafin, slab = author) | |
randem_nw | |
## quota | |
metafin$quota<-0 | |
metafin$quota[metafin$sampling=="online quota"]<-1 | |
summary(metafin$quota) | |
sd(metafin$quota) | |
randem_quota<-rma(yzi,vzi, mods= ~quota,data= metafin, slab = author) | |
randem_quota | |
## average age | |
metafin$age40<-0 | |
metafin$age40[metafin$aveage<40]<-1 | |
summary(metafin$aveage) | |
sd(metafin$aveage) | |
randem_age<- rma(yzi,vzi, mods= ~aveage,data= metafin, slab = author) | |
randem_age | |
randem_age40<- rma(yzi,vzi, mods= ~age40,data= metafin, slab = author) | |
randem_age40 | |
## female percent | |
summary(metafin$femper) | |
sd(metafin$femper) | |
randem_femper<- rma(yzi,vzi, mods= ~femper,data= metafin, slab = author) | |
randem_femper | |
## average education | |
summary(metafin$aveedu) | |
sd(metafin$aveedu,na.rm=TRUE) | |
randem_edu<- rma(yzi,vzi, mods= ~aveedu,data= metafin, slab = author) | |
randem_edu | |
## EU/US nation | |
table(metafin$nation) | |
metafin$euus<-0 | |
metafin$euus[metafin$nation=='Finland'|metafin$nation=='France'|metafin$nation=='UK'| | |
metafin$nation=='Czech'|metafin$nation=='Poland'|metafin$nation=='US'|metafin$nation=='Italy' | |
|metafin$nation=='Serbia'|metafin$nation=='Slovakia']<-1 | |
randem_euus<-rma(yzi,vzi, mods= ~euus,data= metafin, slab = author) | |
randem_euus | |
## moving constant | |
metafin$inveuus<-1-metafin$euus | |
randem_euus<-rma(yzi,vzi, mods= ~inveuus,data= metafin, slab = author) | |
randem_euus | |
## number of controls | |
summary(metafin$ncontrol) | |
sd(metafin$ncontrol) | |
randem_ncon<-rma(yzi,vzi, mods= ~ncontrol,data= metafin, slab = author) | |
randem_ncon | |
## make plots | |
predncon<-predict(randem_ncon, newmods = seq(0,30,1)) | |
ncons<- 1/sqrt(metafin$vzi) | |
nconsize<- (ncons-min(ncons)/(max(ncons)-min(ncons)))/30 | |
plot(metafin$ncontrol,metafin$yzi,xlab = 'Numbers of Controls', | |
ylab = "Correlation Coefficient (R)",xlim = c(0,30),ylim=c(0,0.8),cex=nconsize) | |
lines(seq(0,30,1), predncon$pred, col = "navy") | |
lines(seq(0,30,1), predncon$ci.lb, lty = "dashed", col=" blue") | |
lines(seq(0,30,1), predncon$ci.ub, lty = "dashed", col=" blue") | |
abline(h=0,col='red') | |
## months since 2020.1 | |
metafin$monnumber<-metafin$month+(metafin$year-2020)*12 | |
summary(metafin$monnumber) | |
sd(metafin$monnumber,na.rm = TRUE) | |
## interpolation | |
metafin$monnumberitpl<-metafin$monnumber | |
metafin$monnumberitpl[which(is.na(metafin$monnumberitpl))]<-8.579 | |
summary(metafin$monnumberitpl) | |
randem_mon<-rma(yzi,vzi, mods= ~monnumber,data= metafin, slab = author) | |
randem_mon | |
randem_monitpl<-rma(yzi,vzi, mods= ~monnumberitpl,data= metafin, slab = author) | |
randem_monitpl | |
## plot | |
prednmonitpl<-predict(randem_monitpl, newmods = seq(0,20,1)) | |
ncons<- 1/sqrt(metafin$vzi) | |
nconsize<- (ncons-min(ncons)/(max(ncons)-min(ncons)))/30 | |
plot(metafin$monnumber,metafin$yzi,xlab = 'Numbers of Month Since 2020 Jan.', | |
ylab = "Correlation Coefficient (R)",xlim = c(0,20),ylim=c(0,0.8),cex=nconsize) | |
lines(seq(0,20,1), prednmonitpl$pred, col = "navy") | |
lines(seq(0,20,1), prednmonitpl$ci.lb, lty = "dashed", col=" blue") | |
lines(seq(0,20,1), prednmonitpl$ci.ub, lty = "dashed", col=" blue") | |
abline(h=0,col='red') | |
## type of conspiracy | |
table(metafin$xcontent) | |
metafin$xcontb<-factor(metafin$xcontent, | |
levels = c('Political interests','vaccine','mixed','Bioweapon/man made','Hidden truth','hoax')) | |
randem_xcontb<-rma(yzi,vzi, mods= ~xcontb,data= metafin, slab = author) | |
randem_xcontb | |
predxcontp<-predict(randem_xcontb, newmods = c(0,0,0,0,0)) | |
predxcontp$pred | |
predxcontp$ci.lb | |
predxcontp$ci.ub | |
predxcontv<-predict(randem_xcontb, newmods = c(1,0,0,0,0)) | |
predxcontv$pred | |
predxcontv$ci.lb | |
predxcontv$ci.ub | |
predxcontm<-predict(randem_xcontb, newmods = c(0,1,0,0,0)) | |
predxcontm$pred | |
predxcontm$ci.lb | |
predxcontm$ci.ub | |
predxcontb<-predict(randem_xcontb, newmods = c(0,0,1,0,0)) | |
predxcontb$pred | |
predxcontb$ci.lb | |
predxcontb$ci.ub | |
predxcontht<-predict(randem_xcontb, newmods = c(0,0,0,1,0)) | |
predxcontht$pred | |
predxcontht$ci.lb | |
predxcontht$ci.ub | |
predxcontho<-predict(randem_xcontb, newmods = c(0,0,0,0,1)) | |
predxcontho$pred | |
predxcontho$ci.lb | |
predxcontho$ci.ub | |
table(metafin$xcontent) | |
metafin$xcontnum<-0 | |
metafin$xcontnum[metafin$xcontent=='Political interests']<-1 | |
metafin$xcontnum[metafin$xcontent=='vaccine']<-2 | |
metafin$xcontnum[metafin$xcontent=='mixed']<-3 | |
metafin$xcontnum[metafin$xcontent=='Bioweapon/man made']<-4 | |
metafin$xcontnum[metafin$xcontent=='Hidden truth']<-5 | |
metafin$xcontnum[metafin$xcontent=='hoax']<-6 | |
## plot | |
plot(metafin$xcontnum,metafin$yzi,xlab = 'Type of Conspiracy', | |
ylab = "Correlation Coefficient (R)",ylim=c(-0.3,1.1),cex=nconsize) | |
legend('topleft',cex=0.8, | |
c('1=Political interests','2=Vaccine','3=Mixed','4=Bioweapon/man made','5=Hidden truth','6=Hoax')) | |
lines(c(1,1,1),c(predxcontp$ci.lb,predxcontp$pred,predxcontp$ci.ub),lty=2,col='grey') | |
lines(c(2,2,2),c(predxcontv$ci.lb,predxcontv$pred,predxcontv$ci.ub),lty=2,col='grey') | |
lines(c(3,3,3),c(predxcontm$ci.lb,predxcontm$pred,predxcontm$ci.ub),lty=2,col='grey') | |
lines(c(4,4,4),c(predxcontb$ci.lb,predxcontb$pred,predxcontb$ci.ub),lty=2,col='grey') | |
lines(c(5,5,5),c(predxcontht$ci.lb,predxcontht$pred,predxcontht$ci.ub),lty=2,col='grey') | |
lines(c(6,6,6),c(predxcontho$ci.lb,predxcontho$pred,predxcontho$ci.ub),lty=2,col='grey') | |
points(1,predxcontp$pred,pch=1,lwd=5,col='grey') | |
points(2,predxcontv$pred,pch=1,lwd=5,col='grey') | |
points(3,predxcontm$pred,pch=1,lwd=5,col='grey') | |
points(4,predxcontb$pred,pch=1,lwd=5,col='grey') | |
points(5,predxcontht$pred,pch=1,lwd=5,col='grey') | |
points(6,predxcontho$pred,pch=1,lwd=5,col='grey') | |
abline(h=0,col='red') |