doc and readme

README.md

@@ -13,7 +13,7 @@ In order to install the EDA package on your computer you will have to :
 ``` r
 devtools::install("compo.EDA", build_vignettes = TRUE)
 ```
-will automatically install the package. You might need to additionally install manually the `ggpp` and `sjmisc` packages.
+will automatically install the package and build the vignettes. You might need to additionally install manually the `ggpp` and `sjmisc` packages.
 
 ## How to use compoEDA
 

man/forest_plot_book.Rd

@@ -43,11 +43,11 @@ forest_plot_book(
 
 \item{colors}{<\code{character}> named vector of colors. Each color is named by its group name. Default is NULL.}
 
-\item{other_columns}{<\code{character}> vector of column names from \code{results} and/or \code{dictionary} to be displayed on the table. Default is NULL.
-TODO: improve/change naming of this variable. La c'est bordel, quand c'est TRUE, on affiche \strong{plus} de colonnes!! (les p values). Et en plus ça mélange deux choses, le filter sur uv ou mv. c'est incompréhensible}
+\item{other_columns}{<\code{character}> vector of colums names from \code{results} and/or \code{dictionary} to be displayed on the table. Default is NULL.}
 
-\item{reduce_display}{<\code{logical}> If TRUE, this variable uses the \code{p} and \code{estimate} columns for filtering and display, and \verb{p mv} or \verb{estimate mv} if FALSE. In addition, counterintuitively it displays additionally the p, Signif and p.adjust columns only if \strong{TRUE}, which can be the mv values if these are provided as \code{p}. Default is FALSE.}
+\item{reduce_display}{<\code{logical}> whether to display a reduce display of results}
 }
 \description{
-Filtering is included in the function, based on the \code{p} column if \code{reduce_display} is TRUE and \verb{p uv} if FALSE
+Specificity is that filtering is included in the function, based on the p-value of the \strong{univariable} stats if \code{redcude_display}, otherwise \strong{multivariable} stats.
+However, the OR and HR are displayed based on the \strong{multivariable} stats.
 }