daDoctoR/R/strobe_diff1.R
2018-10-05 13:36:56 +02:00

109 lines
3.1 KiB
R

#' Print regression results according to STROBE
#'
#' Printable table of linear regression analysis of group vs var for meas.
#' @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_diff1()
strobe_diff1<-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(matrix(ncol=7))
if(!is.factor(m)){
for (i in 1:length(levels(g))){
grp<-levels(dat$g)[i]
di<-dat[dat$g==grp,][,-3]
mod<-lm(m~v,data=di)
co<-round(coef(mod)[-1],dec)
lo<-round(confint(mod)[-1,1],dec)
up<-round(confint(mod)[-1,2],dec)
ci<-paste0(co," (",lo," to ",up,")")
amod<-lm(m~.,data=di)
aco<-round(coef(amod)[2],dec)
alo<-round(confint(amod)[2,1],dec)
aup<-round(confint(amod)[2,2],dec)
aci<-paste0(aco," (",alo," to ",aup,")")
nr<-c()
for (r in 1:2){
vr<-levels(di$v)[r]
dr<-di[di$v==vr,]
n<-as.numeric(nrow(dr[!is.na(dr$m),]))
mean<-round(mean(dr$m,na.rm = TRUE),dec-1)
sd<-round(sd(dr$m,na.rm = TRUE),dec-1)
ms<-paste0(mean," (",sd,")")
nr<-c(nr,n,ms)
}
irl<-c(grp,nr,ci,aci)
df<-rbind(df,irl)
names(df)<-c("grp",paste0("N.",substr(levels(v)[1],1,3)),paste0("M.",substr(levels(v)[1],1,3)),paste0("N.",substr(levels(v)[2],1,3)),paste0("M.",substr(levels(v)[2],1,3)),"diff","ad.diff")
}}
if(is.factor(m)){
for (i in 1:length(levels(g))){
grp<-levels(dat$g)[i]
di<-dat[dat$g==grp,][,-3]
mod<-glm(m~v,family=binomial(),data=di)
co<-round(exp(coef(mod)[-1]),dec)
lo<-round(exp(confint(mod)[-1,1]),dec)
up<-round(exp(confint(mod)[-1,2]),dec)
ci<-paste0(co," (",lo," to ",up,")")
amod<-glm(m~.,family=binomial(),data=di)
aco<-round(exp(coef(amod)[2]),dec)
alo<-suppressMessages(round(exp(confint(amod)[2,1]),dec))
aup<-suppressMessages(round(exp(confint(amod)[2,2]),dec))
aci<-paste0(aco," (",alo," to ",aup,")")
nr<-c()
for (r in 1:2){
vr<-levels(di$v)[r]
dr<-di[di$v==vr,]
n<-as.numeric(nrow(dr[!is.na(dr$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<-c(grp,nr,ci,aci)
df<-rbind(df,irl)
names(df)<-c("grp",paste0("N.",substr(levels(v)[1],1,3)),paste0(nl,".",substr(levels(v)[1],1,3)),paste0("N.",substr(levels(v)[2],1,3)),paste0(nl,".",substr(levels(v)[2],1,3)),"OR","ad.OR")
}}
return(df)
}