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92 lines
2.5 KiB
R
92 lines
2.5 KiB
R
#' Print ordinal logistic regression results according to STROBE
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#'
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#' Printable table of ordinal logistic regression analysis oaccording to STROBE. Uses polr() funtion of the MASS-package.
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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 vars variables to compare against. As vector of columnnames.
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#' @param data dataframe of data.
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#' @param dec decimals for results, standard is set to 2. Mean and sd is dec-1.
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#' @keywords olr
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#' @export
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strobe_olr<-function(meas,vars,data,dec=2){
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require(MASS)
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require(dplyr)
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d<-data
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m<-d[,c(meas)]
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v<-d[,c(vars)]
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dat<-data.frame(m,v)
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ma <- polr(m ~ ., data = dat, Hess=TRUE)
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actable <- coef(summary(ma))
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pa <- pnorm(abs(actable[, "t value"]), lower.tail = FALSE) * 2
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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<-pa[1:length(coef(ma))]
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aco<-round(exp(coef(ma)),dec)
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aci<-round(exp(confint(ma)),dec)
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alo<-aci[,1]
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aup<-aci[,2]
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aor_ci<-paste0(aco," (",alo," to ",aup,")")
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dat2<-ma$model[,-1]
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# names(dat2)<-c(var,names(ads))
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nq<-c()
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for (i in 1:ncol(dat2)){
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if (is.factor(dat2[,i])){
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vec<-dat2[,i]
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ns<-names(dat2)[i]
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for (r in 1:length(levels(vec))){
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vr<-levels(vec)[r]
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dr<-vec[vec==vr]
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n<-as.numeric(length(dr))
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nall<-as.numeric(nrow(dat2))
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nl<-paste0(ns,levels(vec)[r])
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pro<-round(n/nall*100,0)
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rt<-paste0(n," (",pro,"%)")
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nq<-rbind(nq,cbind(nl,rt))
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}
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}
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if (!is.factor(dat2[,i])){
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num<-dat2[,i]
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ns<-names(dat2)[i]
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n<-as.numeric(nrow(dat2))
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nall<-as.numeric(nrow(dat2))
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pro<-round(n/nall*100,0)
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rt<-paste0(n," (",pro,"%)")
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nq<-rbind(nq,cbind(ns,rt))
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}
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}
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rnames<-c()
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for (i in 1:ncol(dat2)){
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if (is.factor(dat2[,i])){
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rnames<-c(rnames,names(dat2)[i],paste0(names(dat2)[i],levels(dat2[,i])))
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}
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if (!is.factor(dat2[,i])){
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rnames<-c(rnames,paste0(names(dat2)[i],".all"),names(dat2)[i])
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}
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}
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res<-cbind(aor_ci,apv)
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rest<-data.frame(names=row.names(res),res,stringsAsFactors = F)
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numb<-data.frame(names=nq[,c("nl")],N=nq[,c("rt")],stringsAsFactors = F)
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namt<-data.frame(names=rnames,stringsAsFactors = F)
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coll<-left_join(left_join(namt,numb,by="names"),rest,by="names")
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df<-data.frame(coll)
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names(df)<-c("Variable","N","OR (95 % CI)","p value")
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return(df)
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}
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