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adding p-vals to _byvar
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agdamsbo
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0819d48953
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@ -1,7 +1,7 @@
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Package: daDoctoR
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Type: Package
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Title: FUNCTIONS FOR HEALTH RESEARCH
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Version: 0.1.0.9020
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Version: 0.1.0.9021
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Author@R: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut")))
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Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
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Description: I am a Danish medical doctor involved in neuropsychiatric research.
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@ -1,6 +1,6 @@
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#' Print regression results according to STROBE
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#'
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#' Printable table of three dimensional regression analysis of group vs var for meas. By var.
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#' Printable table of three dimensional regression analysis of group vs var for meas. By var. Includes p-values.
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#' @param meas outcome meassure variable name in data-data.frame as a string. Can be numeric or factor. Result is calculated accordingly.
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#' @param var binary exposure variable to compare against (active vs placebo). As string.
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#' @param groups groups to compare, as string.
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@ -13,100 +13,127 @@
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#' strobe_diff_byvar()
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strobe_diff_byvar<-function(meas,var,group,adj,data,dec=2){
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## Wishlist:
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## -fix confint()
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## meas: sdmt
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## var: rtreat
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## group: genotype
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## for dichotome exposure variable (var)
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d<-data
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m<-d[,c(meas)]
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v<-d[,c(var)]
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g<-d[,c(group)]
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d <- data
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m <- d[, c(meas)]
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v <- d[, c(var)]
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g <- d[, c(group)]
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ads <- d[, c(adj)]
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dat <- data.frame(m, v, g, ads)
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df <- data.frame(grp = c(NA, as.character(levels(g))))
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if (!is.factor(m)) {
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for (i in 1:length(levels(v))) {
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grp <- levels(dat$v)[i]
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di <- dat[dat$v == grp, ][, -2]
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mod <- lm(m ~ g, data = di)
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ads<-d[,c(adj)]
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p <- coef(summary(mod))[2:length(levels(g)),4]
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p<-ifelse(p<0.001,"<0.001",round(p,3))
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p <- ifelse(p<=0.05|p=="<0.001",paste0("*",p),
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ifelse(p>0.05&p<=0.1,paste0(".",p),p))
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pv<-c("-",p)
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dat<-data.frame(m,v,g,ads)
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co <- c("-", round(coef(mod)[-1], dec))
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ci<-round(confint(mod),dec)[2:length(levels(g)),]
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lo <- c("-", ci[,1])
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up <- c("-", ci[,2])
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ci <- paste0(co, " (", lo, " to ", up, ")")
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df<-data.frame(grp=c(NA,as.character(levels(g))))
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amod <- lm(m ~ ., data = di)
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if(!is.factor(m)){
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pa <- coef(summary(amod))[2:length(levels(g)),4]
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pa<-ifelse(pa<0.001,"<0.001",round(pa,3))
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pa <- ifelse(pa<=0.05|pa=="<0.001",paste0("*",pa),
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ifelse(pa>0.05&pa<=0.1,paste0(".",pa),pa))
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apv<-c("-",pa)
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for (i in 1:length(levels(v))){
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grp<-levels(dat$v)[i]
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di<-dat[dat$v==grp,][,-2]
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mod<-lm(m~g,data=di)
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co<-c("-",round(coef(mod)[-1],dec))
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lo<-c("-",round(confint(mod)[-1,1],dec))
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up<-c("-",round(confint(mod)[-1,2],dec))
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ci<-paste0(co," (",lo," to ",up,")")
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amod<-lm(m~.,data=di)
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aco<-c("-",round(coef(amod)[2:length(levels(g))],dec))
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alo<-c("-",round(confint(amod)[2:length(levels(g)),1],dec))
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aup<-c("-",round(confint(amod)[2:length(levels(g)),2],dec))
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aci<-paste0(aco," (",alo," to ",aup,")")
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nr<-c()
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for (r in 1:length(levels(g))){
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vr<-levels(di$g)[r]
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dr<-di[di$g==vr,]
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n<-as.numeric(nrow(dr[!is.na(dr$m),]))
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mean<-round(mean(dr$m,na.rm = TRUE),dec-1)
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sd<-round(sd(dr$m,na.rm = TRUE),dec-1)
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ms<-paste0(mean," (",sd,")")
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nr<-c(nr,n,ms)
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aco <- c("-", round(coef(amod)[2:length(levels(g))],
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dec))
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aci<-round(confint(amod),dec)[2:length(levels(g)),]
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alo <- c("-", aci[,1])
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aup <- c("-", aci[,2])
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aci <- paste0(aco, " (", alo, " to ", aup, ")")
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nr <- c()
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for (r in 1:length(levels(g))) {
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vr <- levels(di$g)[r]
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dr <- di[di$g == vr, ]
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n <- as.numeric(nrow(dr[!is.na(dr$m), ]))
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mean <- round(mean(dr$m, na.rm = TRUE), dec -
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1)
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sd <- round(sd(dr$m, na.rm = TRUE), dec - 1)
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ms <- paste0(mean, " (", sd, ")")
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nr <- c(nr, n, ms)
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}
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irl<-rbind(matrix(grp,ncol=4),cbind(matrix(nr,ncol=2,byrow = TRUE),cbind(ci,aci)))
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colnames(irl)<-c("N","Mean (SD)","Difference","Adjusted Difference")
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df<-cbind(df,irl)
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}}
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if(is.factor(m)){
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for (i in 1:length(levels(v))){
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grp<-levels(dat$v)[i]
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di<-dat[dat$v==grp,][,-2]
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mod<-glm(m~g,family=binomial(),data=di)
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co<-c("-",round(exp(coef(mod)[-1]),dec))
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lo<-c("-",round(exp(confint(mod)[-1,1]),dec))
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up<-c("-",round(exp(confint(mod)[-1,2]),dec))
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ci<-paste0(co," (",lo," to ",up,")")
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amod<-glm(m~.,family=binomial(),data=di)
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aco<-c("-",suppressMessages(round(exp(coef(amod)[2:length(levels(g))]),dec)))
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alo<-c("-",suppressMessages(round(exp(confint(amod)[2:length(levels(g)),1]),dec)))
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aup<-c("-",suppressMessages(round(exp(confint(amod)[2:length(levels(g)),2]),dec)))
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aci<-paste0(aco," (",alo," to ",aup,")")
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nr<-c()
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for (r in 1:length(levels(g))){
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vr<-levels(di$g)[r]
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dr<-di[di$g==vr,]
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n<-as.numeric(nrow(dr[!is.na(dr$m),]))
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nl<-levels(m)[2]
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out<-nrow(dr[dr$m==nl&!is.na(dr$m),])
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pro<-round(out/n*100,0)
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rt<-paste0(out," (",pro,"%)")
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nr<-c(nr,n,rt)
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irl <- rbind(matrix(grp, ncol = 6), cbind(matrix(nr,
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ncol = 2, byrow = TRUE), cbind(ci,pv, aci,apv)))
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colnames(irl) <- c("N",
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"Mean (SD)",
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"Difference",
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"p-value",
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"Adjusted Difference",
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"Adjusted p-value")
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df <- cbind(df, irl)
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}
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irl<-rbind(matrix(grp,ncol=4),cbind(matrix(nr,ncol=2,byrow = TRUE),cbind(ci,aci)))
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colnames(irl)<-c("N",paste0("N.",nl),"OR","Adjusted OR")
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df<-cbind(df,irl)
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}}
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}
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if (is.factor(m)) {
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for (i in 1:length(levels(v))) {
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grp <- levels(dat$v)[i]
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di <- dat[dat$v == grp, ][, -2]
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mod <- glm(m ~ g, family = binomial(), data = di)
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p <- coef(summary(mod))[2:length(levels(g)),4]
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p<-ifelse(p<0.001,"<0.001",round(p,3))
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p <- ifelse(p<=0.05|p=="<0.001",paste0("*",p),
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ifelse(p>0.05&p<=0.1,paste0(".",p),p))
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pv<-c("-",p)
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co <- c("-", round(exp(coef(mod)[-1]), dec))
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ci <- suppressMessages(round(exp(confint(mod)),dec))[2:length(levels(g)),]
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lo <- c("-", ci[,1])
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up <- c("-", ci[,2])
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ci <- paste0(co, " (", lo, " to ", up, ")")
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amod <- glm(m ~ ., family = binomial(), data = di)
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pa <- coef(summary(amod))[2:length(levels(g)),4]
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pa<-ifelse(pa<0.001,"<0.001",round(pa,3))
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pa <- ifelse(pa<=0.05|pa=="<0.001",paste0("*",pa),
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ifelse(pa>0.05&pa<=0.1,paste0(".",pa),pa))
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apv<-c("-",pa)
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aco <- c("-", suppressMessages(round(exp(coef(amod)[2:length(levels(g))]),
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dec)))
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aci <- suppressMessages(round(exp(confint(mod)),dec)[2:length(levels(g)),])
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alo <- c("-", aci[,1])
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aup <- c("-", aci[,2])
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aci <- paste0(aco, " (", alo, " to ", aup, ")")
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nr <- c()
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for (r in 1:length(levels(g))) {
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vr <- levels(di$g)[r]
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dr <- di[di$g == vr, ]
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n <- as.numeric(nrow(dr[!is.na(dr$m), ]))
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nl <- levels(m)[2]
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out <- nrow(dr[dr$m == nl & !is.na(dr$m), ])
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pro <- round(out/n * 100, 0)
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rt <- paste0(out, " (", pro, "%)")
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nr <- c(nr, n, rt)
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}
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irl <- rbind(matrix(grp, ncol = 4), cbind(matrix(nr,
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ncol = 2, byrow = TRUE), cbind(ci,pv, aci,apv)))
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colnames(irl) <- c("N",
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paste0("N.", nl),
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"OR",
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"p-value",
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"Adjusted OR",
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"Adjusted p-value")
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df <- cbind(df, irl)
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}
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}
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return(df)
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}
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