New function for OLR

DESCRIPTION

@@ -10,7 +10,8 @@ Depends: R (>= 3.4.4)
 Imports: broom,
   dplyr,
   epiR,
-  ggplot2
+  ggplot2,
+  MASS
 License: GPL (>= 2)
 Encoding: UTF-8
 LazyData: true

NAMESPACE

@@ -19,3 +19,4 @@ export(rep_olr)
 export(rep_reg_cie)
 export(strobe_diff_bygroup)
 export(strobe_diff_byvar)
+export(strobe_olr)

R/strobe_olr.R

@@ -0,0 +1,139 @@
+#' Print regression results according to STROBE
+#'
+#' Printable table of linear regression analysis of group vs var for meas. By group.
+#' @param meas outcome meassure variable name in data-data.frame as a string. Can be numeric or factor. Result is calculated accordingly.
+#' @param var exposure variable to compare against (active vs placebo). As string.
+#' @param adj variables to adjust for, as string.
+#' @param data dataframe of data.
+#' @param dec decimals for results, standard is set to 2. Mean and sd is dec-1.
+#' @keywords cpr
+#' @export
+#' @examples
+#' strobe_olr()
+
+strobe_olr<-function(meas,var,adj,data,dec=2){
+  #' Ønskeliste:
+  #'
+  #' - Sum af alle, der indgår (Overall N)
+  #' - Ryd op i kode, der der er overflødig %-regning, alternativt, så fiks at NA'er ikke skal regnes med.
+  #'
+  require(MASS)
+  require(dplyr)
+
+  d<-data
+  m<-d[,c(meas)]
+  v<-d[,c(var)]
+
+  ads<-d[,c(adj)]
+  dat<-data.frame(m,v,ads)
+  df<-data.frame(matrix(ncol=4))
+
+  mn <- polr(m ~ v, data = dat, Hess=TRUE)
+  ma <- polr(m ~ ., data = dat, Hess=TRUE)
+
+  ctable <- coef(summary(mn))
+  pa <- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE) * 2
+  pa<-ifelse(pa<0.001,"<0.001",round(pa,3))
+  pa <- ifelse(pa<=0.05|pa=="<0.001",paste0("*",pa),
+               ifelse(pa>0.05&pa<=0.1,paste0(".",pa),pa))
+  pv<-c("REF",pa[1:length(coef(mn))])
+
+  co<-round(exp(coef(mn)),dec)
+  ci<-confint(mn)
+  lo<-round(exp(ci[,1]),dec)
+  up<-round(exp(ci[,2]),dec)
+
+  or_ci<-c("REF",paste0(co," (",lo," to ",up,")"))
+
+  nr<-c()
+
+  for (r in 1:length(levels(dat[,2]))){
+    vr<-levels(dat[,2])[r]
+    dr<-dat[dat[,2]==vr,]
+    n<-as.numeric(nrow(dr))
+
+    ## Af en eller anden grund bliver der talt for mange med.
+    # nall<-as.numeric(nrow(dat[!is.na(dat[,2]),]))
+    nl<-levels(m)[r]
+    # pro<-round(n/nall*100,0)
+    # rt<-paste0(n," (",pro,"%)")
+    nr<-rbind(nr,cbind(nl,n))
+  }
+
+  mms<-data.frame(cbind(nr,or_ci,pv))
+  header<-data.frame(matrix(var,ncol = ncol(mms)))
+  names(header)<-names(mms)
+
+  ls<-list(unadjusted=data.frame(rbind(header,mms)))
+
+  actable <- coef(summary(ma))
+  pa <- pnorm(abs(actable[, "t value"]), lower.tail = FALSE) * 2
+  pa<-ifelse(pa<0.001,"<0.001",round(pa,3))
+  pa <- ifelse(pa<=0.05|pa=="<0.001",paste0("*",pa),
+               ifelse(pa>0.05&pa<=0.1,paste0(".",pa),pa))
+
+  apv<-pa[1:length(coef(ma))]
+
+  aco<-round(exp(coef(ma)),dec)
+  aci<-round(exp(confint(ma)),dec)
+  alo<-aci[,1]
+  aup<-aci[,2]
+  aor_ci<-paste0(aco," (",alo," to ",aup,")")
+
+  dat2<-dat[,-1]
+  # names(dat2)<-c(var,names(ads))
+  nq<-c()
+
+  for (i in 1:ncol(dat2)){
+    if (is.factor(dat2[,i])){
+      vec<-dat2[,i]
+      ns<-names(dat2)[i]
+      for (r in 1:length(levels(vec))){
+        vr<-levels(vec)[r]
+        dr<-vec[vec==vr]
+        n<-as.numeric(length(dr))
+        # nall<-as.numeric(nrow(dat[!is.na(dat2[,c(ns)]),]))
+        nl<-paste0(ns,levels(vec)[r])
+        # pro<-round(n/nall*100,0)
+        # rt<-paste0(n," (",pro,"%)")
+        nq<-rbind(nq,cbind(nl,n))
+      }
+    }
+    if (!is.factor(dat2[,i])){
+      num<-dat2[,i]
+      ns<-names(dat2)[i]
+      nall<-as.numeric(nrow(dat[!is.na(dat2[,c(ns)]),]))
+      nq<-rbind(nq,cbind(ns,nall))
+    }
+  }
+
+  rnames<-c()
+
+  for (i in 1:ncol(dat2)){
+    if (is.factor(dat2[,i])){
+      rnames<-c(rnames,names(dat2)[i],paste0(names(dat2)[i],levels(dat2[,i])))
+    }
+    if (!is.factor(dat2[,i])){
+      rnames<-c(rnames,paste0(names(dat2)[i],".all"),names(dat2)[i])
+    }
+  }
+  res<-cbind(aor_ci,apv)
+  rest<-data.frame(names=row.names(res),res,stringsAsFactors = F)
+
+  numb<-data.frame(names=nq[,c("nl")],N=nq[,c("n")],stringsAsFactors = F)
+  namt<-data.frame(names=rnames,stringsAsFactors = F)
+
+  coll<-left_join(left_join(namt,numb,by="names"),rest,by="names")
+
+  header<-data.frame(matrix("Adjusted",ncol = ncol(coll)))
+  names(header)<-names(coll)
+
+  ls$adjusted<-data.frame(rbind(header,coll))
+
+  fnames<-c("Variable","N","OR (95 % CI)","p value")
+
+  names(ls$unadjusted)<-fnames
+  names(ls$adjusted)<-fnames
+
+  return(ls)
+}

man/strobe_olr.Rd

@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/strobe_olr.R
+\name{strobe_olr}
+\alias{strobe_olr}
+\title{Print regression results according to STROBE}
+\usage{
+strobe_olr(meas, var, adj, data, dec = 2)
+}
+\arguments{
+\item{meas}{outcome meassure variable name in data-data.frame as a string. Can be numeric or factor. Result is calculated accordingly.}
+
+\item{var}{exposure variable to compare against (active vs placebo). As string.}
+
+\item{adj}{variables to adjust for, as string.}
+
+\item{data}{dataframe of data.}
+
+\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
+}
+\description{
+Printable table of linear regression analysis of group vs var for meas. By group.
+}
+\keyword{cpr}