New function strobe_diff_twodim

NAMESPACE

@@ -19,4 +19,5 @@ export(rep_olr)
 export(rep_reg_cie)
 export(strobe_diff_bygroup)
 export(strobe_diff_byvar)
+export(strobe_diff_twodim)
 export(strobe_olr)

R/strobe_diff_twodim.R

@@ -0,0 +1,105 @@
+#' Print regression results according to STROBE
+#'
+#' Printable table of regression analysis by group for meas. Detects wether to perform logistic or linear regression.
+#' @param meas outcome meassure variable name in data-data.frame as a string. Can be numeric or factor. Result is calculated accordingly.
+#' @param groups groups to compare, 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_diff_byvar()
+
+strobe_diff_twodim<-function(meas,group,adj,data,dec=2){
+  ## meas: sdmt
+  ## var: rtreat
+  ## group: genotype
+  ## for dichotome exposure variable (var)
+
+  d<-data
+  m<-d[,c(meas)]
+  g<-d[,c(group)]
+
+  ads<-d[,c(adj)]
+
+  dat<-data.frame(m,g,ads)
+
+  df<-data.frame(grp=c(group,as.character(levels(g))))
+
+  if(!is.factor(m)){
+
+    mod<-lm(m~g,data=dat)
+    ci<-confint(mod)
+    co<-round(coef(mod)[-1],dec)
+    lo<-round(ci[-1,1],dec)
+    up<-round(ci[-1,2],dec)
+
+    or_ci<-c("0",paste0(co," (",lo," to ",up,")"))
+
+    amod<-lm(m~.,data=dat)
+    aci<-confint(amod)
+    aco<-round(coef(amod)[2:length(levels(g))],dec)
+    alo<-round(aci[2:length(levels(g)),1],dec)
+    aup<-round(aci[2:length(levels(g)),2],dec)
+
+    aor_ci<-c("0",paste0(aco," (",alo," to ",aup,")"))
+
+    nr<-c()
+
+    for (r in 1:length(levels(g))){
+      vr<-levels(dat$g)[r]
+      dr<-dat[dat$g==vr,]
+      n<-as.numeric(nrow(dr[!is.na(dr$m),]))
+      mean<-round(mean(dr$m,na.rm = TRUE),dec-1)
+      sd<-round(sd(dr$m,na.rm = TRUE),dec-1)
+      ms<-paste0(mean," (",sd,")")
+
+      nr<-c(nr,n,ms)
+    }
+    irl<-rbind(matrix(NA,ncol=4),cbind(matrix(nr,ncol=2,byrow = TRUE),cbind(or_ci,aor_ci)))
+    colnames(irl)<-c("N","Mean (SD)","Difference","Adjusted Difference")
+    df<-cbind(df,irl)
+    ls<-list(linear.regression=df)
+  }
+
+  if(is.factor(m)){
+
+    mod<-glm(m~g,family=binomial(),data=di)
+    ci<-confint(mod)
+    co<-round(coef(mod)[-1],dec)
+    lo<-round(ci[-1,1],dec)
+    up<-round(ci[-1,2],dec)
+
+    or_ci<-c("0",paste0(co," (",lo," to ",up,")"))
+
+    amod<-glm(m~.,family=binomial(),data=di)
+    aci<-confint(amod)
+    aco<-round(coef(amod)[2:length(levels(g))],dec)
+    alo<-round(aci[2:length(levels(g)),1],dec)
+    aup<-round(aci[2:length(levels(g)),2],dec)
+
+    aor_ci<-c("0",paste0(aco," (",alo," to ",aup,")"))
+
+    nr<-c()
+
+    for (r in 1:length(levels(g))){
+      vr<-levels(dat$g)[r]
+      dr<-dat[dat$g==vr,]
+      n<-as.numeric(nrow(dr[!is.na(dr$m),]))
+      nl<-levels(m)[2]
+      out<-nrow(dr[dr$m==nl&!is.na(dr$m),])
+      pro<-round(out/n*100,0)
+      rt<-paste0(out," (",pro,"%)")
+
+      nr<-c(nr,n,rt)
+    }
+    irl<-rbind(matrix(NA,ncol=4),cbind(matrix(nr,ncol=2,byrow = TRUE),cbind(or_ci,aor_ci)))
+    colnames(irl)<-c("N",paste0("N.",nl),"OR","Adjusted OR")
+    df<-cbind(df,irl)
+    ls<-list(logistic.regression=df)
+  }
+
+  ls$adjustments<-dput(names(ads))
+  return(ls)
+}

man/plot_ord_odds.Rd

@@ -4,7 +4,7 @@
 \alias{plot_ord_odds}
 \title{Forrest plot from ordinal logistic regression}
 \usage{
-plot_ord_odds(x, title = NULL, dec = 3, lbls = NULL)
+plot_ord_odds(x, title = NULL, dec = 3, lbls = NULL, short = FALSE)
 }
 \arguments{
 \item{x}{ordinal logistic regression model.}
@@ -14,6 +14,8 @@ plot_ord_odds(x, title = NULL, dec = 3, lbls = NULL)
 \item{dec}{decimals for labels}
 
 \item{lbls}{labels for variable names. Carefull, as the right order is not checked automatically!}
+
+\item{short}{flag to half number of ticks on horizontal axis.}
 }
 \description{
 Heavily inspired by https://www.r-bloggers.com/plotting-odds-ratios-aka-a-forrestplot-with-ggplot2/

man/strobe_diff_twodim.Rd

@@ -0,0 +1,26 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/strobe_diff_twodim.R
+\name{strobe_diff_twodim}
+\alias{strobe_diff_twodim}
+\title{Print regression results according to STROBE}
+\usage{
+strobe_diff_twodim(meas, group, 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{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.}
+
+\item{groups}{groups to compare, as string.}
+}
+\description{
+Printable table of regression analysis by group for meas. Detects wether to perform logistic or linear regression.
+}
+\examples{
+strobe_diff_byvar()
+}
+\keyword{cpr}