mean_cl_boot; compare2numvars

.gitignore

@@ -1,6 +1,7 @@
-.Rproj.user
-.Rhistory
-.RData
-.Ruserdata
-inst/doc
-wrappedtools.Rproj
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+inst/doc
+wrappedtools.Rproj
+.DS_Store

DESCRIPTION

@@ -22,6 +22,11 @@ Authors@R: c(
            family = "Asser",
            role = c("aut"),
            email = "billyasser@hotmail.co.uk",
+           comment = ""),
+    person(given = "Franziska",
+           family = "Eidloth",
+           role = c("aut"),
+           email = "franziska.eidloth@gmail.com",
            comment = ""))
 Maintainer: Andreas Busjahn <andreas@busjahn.net>
 License: GPL-3

NAMESPACE

@@ -28,6 +28,7 @@ export(logrange_12357)
 export(logrange_15)
 export(logrange_5)
 export(markSign)
+export(mean_cl_boot)
 export(meansd)
 export(meanse)
 export(median_cl_boot)

NEWS.md

@@ -1,5 +1,9 @@
 #wrappedtools 0.9.7
 - function identical_cols to find and remove duplicated columns
+- function compare2numvars can now additionally calculate confidence intervals
+- function compare2numvars now has the additional option for a singleline or stacked display
+- new function mean_cl_boot which calculates the mean and confidence intervals
+- function median_cl_boot now has an additional round option
 
 #wrappedtools 0.9.6
 - function ksnormal now uses Lilliefors test by default

R/descriptives.R

@@ -255,25 +255,35 @@ se_median <- function(x) {
 #' @param conf confidence interval with default 95%.
 #' @param type type for function boot.ci.
 #' @param nrepl number of bootstrap replications, defaults to 1000.
+#' @param round logical, applies [roundR] function to results. Output is character.
+#' @param roundDig number of relevant digits for function [roundR].
 #'
 #' @return A tibble with one row and three columns: Median, CIlow, CIhigh.
 #'
 #' @examples
 #' # basic usage of median_cl_boot
 #' median_cl_boot(x = mtcars$wt)
 #' @export
-median_cl_boot <- function(x, conf = 0.95, type = "basic", nrepl = 10^3) {
+median_cl_boot <- function(x, conf = 0.95, type = "basic", nrepl = 10^3, round = FALSE, roundDig = 2) {
   x <- na.omit(x)
   lconf <- (1 - conf) / 2
   uconf <- 1 - lconf
   bmedian <- function(x, ind) median(x[ind], na.rm = TRUE)
   bt <- boot::boot(x, bmedian, nrepl)
   bb <- boot::boot.ci(bt, type = type)
-  tibble(
-    Median = median(x, na.rm = TRUE),
-    CIlow = quantile(bt$t, lconf),
-    CIhigh = quantile(bt$t, uconf)
-  )
+  if (round) {
+    return(tibble(
+      Median = roundR(median(x, na.rm = TRUE), level = roundDig),
+      CIlow = roundR(quantile(bt$t, lconf), level = roundDig),
+      CIhigh = roundR(quantile(bt$t, uconf), level = roundDig)
+    ))
+  } else {
+    return(tibble(
+      Median = median(x, na.rm = TRUE),
+      CIlow = quantile(bt$t, lconf),
+      CIhigh = quantile(bt$t, uconf)
+    ))
+  }
 }
 #' Rename output from \link{median_cl_boot} for use in ggplot.
 #'
@@ -296,6 +306,47 @@ median_cl_boot_gg <- function(x){
     rename(y="Median",ymin="CIlow",ymax="CIhigh")
   return(out)
 }
+
+#' Compute confidence interval of mean by bootstrapping.
+#'
+#' \code{mean_cl_boot} computes lower and upper confidence limits for the
+#' estimated mean, based on bootstrapping.
+#'
+#' @param x Data for computation.
+#' @param conf confidence interval with default 95%.
+#' @param type type for function boot.ci.
+#' @param nrepl number of bootstrap replications, defaults to 1000.
+#' @param round logical, applies [roundR] function to results. Output is character.
+#' @param roundDig Number of relevant digits for functio [roundR].
+#'
+#' @return A tibble with one row and three columns: Mean, CIlow, CIhigh.
+#'
+#' @examples
+#' # basic usage of mean_cl_boot
+#' mean_cl_boot(x = mtcars$wt)
+#' @export
+mean_cl_boot <- function(x, conf = 0.95, type = "basic", nrepl = 10^3,
+                         round = FALSE, roundDig = 2) ## 
+{
+  x <- na.omit(x)
+  lconf <- (1 - conf)/2
+  uconf <- 1 - lconf
+  bmean <- function(x, ind) mean(x[ind], na.rm = TRUE)
+  bt <- boot::boot(x, bmean, nrepl)
+  bb <- boot::boot.ci(bt, type = type)
+
+  if(round){
+    tibble(Mean = roundR(mean(x, na.rm = TRUE), level = roundDig), 
+           CIlow = roundR(quantile(bt$t, lconf), level = roundDig), 
+           CIhigh = roundR(quantile(bt$t, uconf), level = roundDig)
+    )
+  } else{
+    tibble(Mean = mean(x, na.rm = TRUE), 
+           CIlow = quantile(bt$t, lconf), 
+           CIhigh = quantile(bt$t, uconf)
+    )
+  }
+}
 #' Compute absolute and relative frequencies.
 #'
 #' \code{cat_desc_stats} computes absolute and relative frequencies for

R/pkgstart.R

@@ -40,7 +40,7 @@ NULL
 #' @importFrom rlist list.append
 NULL 
 
-#' @importFrom forcats fct_lump_n fct_drop
+#' @importFrom forcats fct_lump_n fct_drop fct_inorder
 NULL
 
 #' @importFrom grDevices boxplot.stats