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agdamsbo 2019-11-08 11:01:35 +01:00
parent 84e390f378
commit 80975f65e7
2 changed files with 1 additions and 22 deletions
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12
R/rep_glm.R
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@ -9,17 +9,7 @@
#' @param fixed.var flag to set "vars" as fixed in the model. When FALSE, then true bivariate logistic regression is performed.
#' @keywords logistic
#' @export
#' @examples
#' l<-50
#' y<-factor(rep(c("a","b"),l))
#' x<-rnorm(length(y), mean=50, sd=10)
#' v1<-factor(rep(c("r","s"),length(y)/2))
#' v2<-sample(1:100, length(y), replace=FALSE)
#' v3<-as.numeric(1:length(y))
#' d<-data.frame(y,x,v1,v2,v3)
#' preds<-c("v1","v2","x")
#' rep_glm(meas="y",vars="v3",string=preds,ci=F,data=d)
#'
rep_glm<-function(meas,vars=NULL,string,ci=FALSE,data,fixed.var=FALSE){

11
man/rep_glm.Rd
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@ -23,15 +23,4 @@ rep_glm(meas, vars = NULL, string, ci = FALSE, data,
\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.
}
\examples{
l<-50
y<-factor(rep(c("a","b"),l))
x<-rnorm(length(y), mean=50, sd=10)
v1<-factor(rep(c("r","s"),length(y)/2))
v2<-sample(1:100, length(y), replace=FALSE)
v3<-as.numeric(1:length(y))
d<-data.frame(y,x,v1,v2,v3)
preds<-c("v1","v2","x")
rep_glm(meas="y",vars="v3",string=preds,ci=F,data=d)
}
\keyword{logistic}