mirror of
https://github.com/agdamsbo/daDoctoR.git
synced 2024-11-21 19:30:22 +01:00
99 lines
2.4 KiB
R
99 lines
2.4 KiB
R
#' A repeated ordinal logistic regression function
|
|
#'
|
|
#' For bivariate analyses. The confint() function is rather slow, causing the whole function to hang when including many predictors and calculating the ORs with CI.
|
|
#' @param meas Effect meassure. Input as c() of columnnames, use dput().
|
|
#' @param vars variables in model. Input as c() of columnnames, use dput().
|
|
#' @param string variables to test. Input as c() of columnnames, use dput().
|
|
#' @param ci flag to get results as OR with 95% confidence interval.
|
|
#' @param data data frame to pull variables from.
|
|
#' @keywords olr
|
|
#' @export
|
|
|
|
rep_olr<-function(meas,vars,string,ci=FALSE,data){
|
|
|
|
require(broom)
|
|
require(MASS)
|
|
|
|
d<-data
|
|
x<-data.frame(d[,c(string)])
|
|
v<-data.frame(d[,c(vars)])
|
|
names(v)<-c(vars)
|
|
y<-d[,c(meas)]
|
|
dt<-cbind(y,v)
|
|
m1<-length(coef(polr(y~.,data = dt,Hess=TRUE)))
|
|
|
|
if (!is.factor(y)){stop("y should be a factor!")}
|
|
|
|
if (ci==TRUE){
|
|
|
|
df<-data.frame(matrix(ncol = 3))
|
|
names(df)<-c("pred","or_ci","pv")
|
|
|
|
for(i in 1:ncol(x)){
|
|
dat<-cbind(dt,x[,i])
|
|
m<-polr(y~.,data=dat,Hess=TRUE)
|
|
|
|
ctable <- coef(summary(m))
|
|
|
|
l<-suppressMessages(round(exp(confint(m))[-c(1:m1),1],2))
|
|
u<-suppressMessages(round(exp(confint(m))[-c(1:m1),2],2))
|
|
or<-round(exp(coef(m))[-c(1:m1)],2)
|
|
or_ci<-paste0(or," (",l," to ",u,")")
|
|
|
|
p <- (pnorm(abs(ctable[, "t value"]), lower.tail = FALSE) * 2)[1:length(coef(m))]
|
|
pv<-round(p[-c(1:m1)],3)
|
|
|
|
|
|
x1<-x[,i]
|
|
|
|
if (is.factor(x1)){
|
|
pred<-paste(names(x)[i],levels(x1)[-1],sep = "_")}
|
|
|
|
else {pred<-names(x)[i]}
|
|
|
|
df<-rbind(df,cbind(pred,or_ci,pv))
|
|
}}
|
|
|
|
if (ci==FALSE){
|
|
|
|
df<-data.frame(matrix(ncol = 3))
|
|
names(df)<-c("pred","b","pv")
|
|
|
|
for(i in 1:ncol(x)){
|
|
dat<-cbind(dt,x[,i])
|
|
m<-polr(y~.,data=dat,Hess=TRUE)
|
|
|
|
ctable <- coef(summary(m))
|
|
|
|
b<-round(coef(m)[-c(1:m1)],2)
|
|
|
|
p <- (pnorm(abs(ctable[, "t value"]), lower.tail = FALSE) * 2)[1:length(coef(m))]
|
|
pv<-round(p[-c(1:m1)],3)
|
|
|
|
x1<-x[,i]
|
|
|
|
if (is.factor(x1)){
|
|
pred<-paste(names(x)[i],levels(x1)[-1],sep = "_")
|
|
}
|
|
|
|
else {pred<-names(x)[i]}
|
|
|
|
df<-rbind(df,cbind(pred,b,pv))
|
|
|
|
}}
|
|
|
|
pa<-as.numeric(df[,c("pv")])
|
|
t <- ifelse(pa<=0.1,"include","drop")
|
|
pa<-ifelse(pa<0.001,"<0.001",pa)
|
|
pa <- ifelse(pa<=0.05|pa=="<0.001",paste0("*",pa),
|
|
ifelse(pa>0.05&pa<=0.1,paste0(".",pa),pa))
|
|
|
|
r<-data.frame(df[,1:2],pa,t)[-1,]
|
|
|
|
return(r)
|
|
}
|
|
|
|
|
|
|
|
|