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adding example data

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agdamsbo 2018-10-04 10:35:05 +02:00
parent cc3ad2c44a
commit 5505baae5a
2 changed files with 19 additions and 2 deletions
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11
R/rep_glm.R
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@ -9,7 +9,15 @@
#' @keywords logistic regression
#' @export
#' @examples
#' rep_glm()
#' l<-5
#' 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<-dput(names(d)[3:ncol(d)])
#' rep_glm(meas="y",vars="x",string=preds,ci=FALSE,data=df)
rep_glm<-function(meas,vars,string,ci=FALSE,data){
## x is data.frame of predictors, y is vector of an aoutcome as a factor
@ -88,3 +96,4 @@ rep_glm<-function(meas,vars,string,ci=FALSE,data){
return(r)
}

10
man/rep_glm.Rd
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@ -21,7 +21,15 @@ rep_glm(meas, vars, string, ci = FALSE, data)
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{
rep_glm()
l<-5
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<-dput(names(d)[3:ncol(d)])
rep_glm(meas="y",vars="x",string=preds,ci=FALSE,data=df)
}
\keyword{logistic}
\keyword{regression}