updates

R/strobe_diff_bygroup.R

@@ -1,6 +1,6 @@
 #' Print regression results according to STROBE
 #'
-#' Printable table of linear regression analysis of group vs var for meas.
+#' 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 groups groups to compare, as string.
@@ -10,9 +10,9 @@
 #' @keywords cpr
 #' @export
 #' @examples
-#' strobe_diff1()
+#' strobe_diff_bygroup()
 
-strobe_diff1<-function(meas,var,group,adj,data,dec=2){
+strobe_diff_bygroup<-function(meas,var,group,adj,data,dec=2){
   ## meas: sdmt
   ## var: rtreat
   ## group: genotype

R/strobe_diff_byvar.R

@@ -0,0 +1,108 @@
+#' Print regression results according to STROBE
+#'
+#' Printable table of linear regression analysis of group vs var for meas. By var.
+#' @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 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_byvar<-function(meas,var,group,adj,data,dec=2){
+  ## meas: sdmt
+  ## var: rtreat
+  ## group: genotype
+  ## for dichotome exposure variable (var)
+
+  d<-data
+  m<-d[,c(meas)]
+  v<-d[,c(var)]
+  g<-d[,c(group)]
+
+  ads<-d[,c(adj)]
+
+  dat<-data.frame(m,v,g,ads)
+
+  df<-data.frame(grp=c(NA,as.character(levels(g))))
+
+  if(!is.factor(m)){
+
+    for (i in 1:length(levels(v))){
+      grp<-levels(dat$v)[i]
+      di<-dat[dat$v==grp,][,-2]
+
+      mod<-lm(m~g,data=di)
+      co<-c("-",round(coef(mod)[-1],dec))
+      lo<-c("-",round(confint(mod)[-1,1],dec))
+      up<-c("-",round(confint(mod)[-1,2],dec))
+
+      ci<-paste0(co," (",lo," to ",up,")")
+
+      amod<-lm(m~.,data=di)
+      aco<-c("-",round(coef(amod)[2:length(levels(g))],dec))
+      alo<-c("-",round(confint(amod)[2:length(levels(g)),1],dec))
+      aup<-c("-",round(confint(amod)[2:length(levels(g)),2],dec))
+
+      aci<-paste0(aco," (",alo," to ",aup,")")
+
+      nr<-c()
+
+      for (r in 1:length(levels(g))){
+        vr<-levels(di$g)[r]
+        dr<-di[di$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$m,na.rm = TRUE),dec-1)
+        ms<-paste0(mean," (",sd,")")
+
+        nr<-c(nr,n,ms)
+      }
+      irl<-rbind(matrix(grp,ncol=4),cbind(matrix(nr,ncol=2,byrow = TRUE),cbind(ci,aci)))
+      colnames(irl)<-c("N","Mean (SD)","Difference","Adjusted Difference")
+      df<-cbind(df,irl)
+    }}
+
+  if(is.factor(m)){
+
+    for (i in 1:length(levels(v))){
+      grp<-levels(dat$v)[i]
+      di<-dat[dat$v==grp,][,-2]
+
+      mod<-glm(m~g,family=binomial(),data=di)
+      co<-c("-",round(exp(coef(mod)[-1]),dec))
+      lo<-c("-",round(exp(confint(mod)[-1,1]),dec))
+      up<-c("-",round(exp(confint(mod)[-1,2]),dec))
+
+      ci<-paste0(co," (",lo," to ",up,")")
+
+      amod<-glm(m~.,family=binomial(),data=di)
+      aco<-c("-",suppressMessages(round(exp(coef(amod)[2:length(levels(g))]),dec)))
+      alo<-c("-",suppressMessages(round(exp(confint(amod)[2:length(levels(g)),1]),dec)))
+      aup<-c("-",suppressMessages(round(exp(confint(amod)[2:length(levels(g)),2]),dec)))
+
+      aci<-paste0(aco," (",alo," to ",aup,")")
+
+      nr<-c()
+
+      for (r in 1:length(levels(g))){
+        vr<-levels(di$g)[r]
+        dr<-di[di$g==vr,]
+        n<-as.numeric(nrow(dr[!is.na(dr$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(grp,ncol=4),cbind(matrix(nr,ncol=2,byrow = TRUE),cbind(ci,aci)))
+      colnames(irl)<-c("N",paste0("N.",nl),"OR","Adjusted OR")
+      df<-cbind(df,irl)
+    }}
+
+  return(df)
+}