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universalising..

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agdamsbo 2018-10-04 10:10:35 +02:00
parent 39dc511e12
commit af0c04e5ce
2 changed files with 15 additions and 16 deletions
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23
R/rep_glm.R
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@ -1,15 +1,17 @@
#' A repeated logistic regression function
#'
#' @description 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 y Effect meassure.
#' @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 logistic regression
#' @export
#' @examples
#' rep_glm()
rep_glm<-function(y,vars,string,ci=FALSE,data){
rep_glm<-function(meas,vars,string,ci=FALSE,data){
## x is data.frame of predictors, y is vector of an aoutcome as a factor
## output is returned as coefficient, or if or=TRUE as OR with 95 % CI.
##
@ -17,8 +19,9 @@ rep_glm<-function(y,vars,string,ci=FALSE,data){
require(dplyr)
d<-data
x<-select(d,one_of(c(string)))
v<-select(d,one_of(c(vars)))
x<-data.frame(d[,c(string)])
v<-data.frame(d[,c(vars)])
y<-d[,c(meas)]
dt<-cbind(y,v)
m1<-length(coef(glm(y~.,family = binomial(),data = dt)))
@ -30,30 +33,22 @@ rep_glm<-function(y,vars,string,ci=FALSE,data){
names(df)<-c("pred","or_ci","pv")
for(i in 1:ncol(x)){
dat<-cbind(dt,x[,i])
m<-glm(y~.,family = binomial(),data=dat)
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,")")
pv<-round(tidy(m)$p.value[-c(1:m1)],3)
x1<-x[,i]
if (is.factor(x1)){
pred<-paste(names(x)[i],levels(x1)[-1],sep = "_")
}
pred<-paste(names(x)[i],levels(x1)[-1],sep = "_")}
else {pred<-names(x)[i]}
df<-rbind(df,cbind(pred,or_ci,pv))
}}
df<-rbind(df,cbind(pred,or_ci,pv))}}
if (ci==FALSE){

8
man/rep_glm.Rd
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@ -4,14 +4,18 @@
\alias{rep_glm}
\title{A repeated logistic regression function}
\usage{
rep_glm(y, vars, string, ci = FALSE, data)
rep_glm(meas, vars, string, ci = FALSE, data)
}
\arguments{
\item{y}{Effect meassure.}
\item{meas}{Effect meassure. Input as c() of columnnames, use dput().}
\item{vars}{variables in model. Input as c() of columnnames, use dput().}
\item{string}{variables to test. Input as c() of columnnames, use dput().}
\item{ci}{flag to get results as OR with 95% confidence interval.}
\item{data}{data frame to pull variables from.}
}
\description{
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.