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R/cie_test.R

@@ -5,7 +5,6 @@
 #' @param v1 Main variable in model
 #' @param string String of columnnames from dataframe to include. Use dput().
 #' @keywords change-in-estimate
-#'
 #' @examples
 #' l<-5
 #' y<-factor(rep(c("a","b"),l))
@@ -16,9 +15,7 @@
 #' d<-data.frame(y,x,v1,v2,v3)
 #' preds<-dput(names(d)[3:ncol(d)])
 #' cie_test(meas="y",vars="x",string=preds,data=d,logistic = TRUE,cut = 0.1)
-#'
 #' @export
-#'
 
 cie_test<-function(meas,vars,string,data,logistic=FALSE,cut=0.1){
 

R/rep_glm.R

@@ -6,9 +6,7 @@
 #' @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
-#'
 #' @examples
 #' l<-5
 #' y<-factor(rep(c("a","b"),l))
@@ -19,9 +17,7 @@
 #' 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)
-#'
 #' @export
-#'
 
 rep_glm<-function(meas,vars,string,ci=FALSE,data){
   ## x is data.frame of predictors, y is vector of an aoutcome as a factor

man/cie_test.Rd

@@ -26,6 +26,5 @@ v3<-as.numeric(1:length(y))
 d<-data.frame(y,x,v1,v2,v3)
 preds<-dput(names(d)[3:ncol(d)])
 cie_test(meas="y",vars="x",string=preds,data=d,logistic = TRUE,cut = 0.1)
-
 }
 \keyword{change-in-estimate}

man/rep_glm.Rd

@@ -30,7 +30,6 @@ 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}