From 02429bc7968b57f1f66ef88c09ae6141ad60dcaf Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Fri, 10 May 2024 00:00:28 +0200
Subject: [PATCH] fix

---
 NAMESPACE      |  2 --
 R/boot_ci.R    | 23 ++++++++++++++---------
 R/gmd.R        | 23 +++++++++++------------
 man/boot_ci.Rd | 29 ++++++++++++++++-------------
 man/gmd.Rd     |  4 ++--
 5 files changed, 43 insertions(+), 38 deletions(-)

diff --git a/NAMESPACE b/NAMESPACE
index 3de2e0c..3fe93bc 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -123,9 +123,7 @@ importFrom(performance,mse)
 importFrom(performance,rmse)
 importFrom(purrr,map)
 importFrom(purrr,map_dbl)
-importFrom(purrr,map_df)
 importFrom(purrr,map_lgl)
-importFrom(sjmisc,is_empty)
 importFrom(sjmisc,is_float)
 importFrom(sjmisc,str_contains)
 importFrom(sjmisc,typical_value)
diff --git a/R/boot_ci.R b/R/boot_ci.R
index ba3cf81..dd8254e 100644
--- a/R/boot_ci.R
+++ b/R/boot_ci.R
@@ -61,11 +61,14 @@
 #' bs <- bootstrap(efc, 100)
 #'
 #' # now run models for each bootstrapped sample
-#' bs$models <- map(bs$strap, ~lm(neg_c_7 ~ e42dep + c161sex, data = .x))
+#' bs$models <- lapply(
+#'   bs$strap,
+#'   function(.x) lm(neg_c_7 ~ e42dep + c161sex, data = .x)
+#' )
 #'
 #' # extract coefficient "dependency" and "gender" from each model
-#' bs$dependency <- map_dbl(bs$models, ~coef(.x)[2])
-#' bs$gender <- map_dbl(bs$models, ~coef(.x)[3])
+#' bs$dependency <- vapply(bs$models, function(x) coef(x)[2], numeric(1))
+#' bs$gender <- vapply(bs$models, function(x) coef(x)[3], numeric(1))
 #'
 #' # get bootstrapped confidence intervals
 #' boot_ci(bs$dependency)
@@ -76,9 +79,9 @@
 #'
 #' # alternative function calls.
 #' boot_ci(bs$dependency)
-#' boot_ci(bs, dependency)
-#' boot_ci(bs, dependency, gender)
-#' boot_ci(bs, dependency, gender, method = "q")
+#' boot_ci(bs, "dependency")
+#' boot_ci(bs, c("dependency", "gender"))
+#' boot_ci(bs, c("dependency", "gender"), method = "q")
 #'
 #'
 #' # compare coefficients
@@ -130,13 +133,15 @@
 #'   # compute the CI for all bootstrapped model coefficients
 #'   boot_ci()}
 #' @export
-boot_ci <- function(data, ..., method = c("dist", "quantile"), ci.lvl = 0.95) {
-  insight::check_if_installed("dplyr")
+boot_ci <- function(data, select = NULL, method = c("dist", "quantile"), ci.lvl = 0.95) {
   # match arguments
   method <- match.arg(method)
 
   # evaluate arguments, generate data
-  .dat <- get_dot_data(data, dplyr::quos(...))
+  if (is.null(select))
+    .dat <- as.data.frame(data)
+  else
+    .dat <- data[select]
 
   # compute confidence intervals for all values
   transform_boot_result(lapply(.dat, function(x) {
diff --git a/R/gmd.R b/R/gmd.R
index 2fed09a..98ad9c5 100644
--- a/R/gmd.R
+++ b/R/gmd.R
@@ -21,21 +21,20 @@
 #' @examples
 #' data(efc)
 #' gmd(efc$e17age)
-#' gmd(efc, e17age, c160age, c12hour)
+#' gmd(efc, c("e17age", "c160age", "c12hour"))
 #'
-#' @importFrom purrr map_df
-#' @importFrom sjmisc is_empty
 #' @export
-gmd <- function(x, ...) {
-  insight::check_if_installed("dplyr")
- # evaluate dots
-  qs <- dplyr::quos(...)
-  if (!sjmisc::is_empty(qs)) x <- suppressMessages(dplyr::select(x, !!!qs))
-
-  if (is.data.frame(x))
-    purrr::map_df(x, gmd_helper)
-  else
+gmd <- function(x, select = NULL) {
+  if (is.data.frame(x)) {
+    do.call(rbind, lapply(select, function(i) {
+      data.frame(
+        variable = i,
+        gmd = gmd_helper(x[[i]])
+      )
+    }))
+  } else {
     gmd_helper(x)
+  }
 }
 
 
diff --git a/man/boot_ci.Rd b/man/boot_ci.Rd
index 7f4c252..4d57d31 100644
--- a/man/boot_ci.Rd
+++ b/man/boot_ci.Rd
@@ -7,7 +7,7 @@
 \alias{boot_est}
 \title{Standard error and confidence intervals for bootstrapped estimates}
 \usage{
-boot_ci(data, ..., method = c("dist", "quantile"), ci.lvl = 0.95)
+boot_ci(data, select = NULL, method = c("dist", "quantile"), ci.lvl = 0.95)
 
 boot_se(data, ...)
 
@@ -19,12 +19,6 @@ boot_est(data, ...)
 \item{data}{A data frame that containts the vector with bootstrapped
 estimates, or directly the vector (see 'Examples').}
 
-\item{...}{Optional, unquoted names of variables with bootstrapped estimates.
-Required, if either \code{data} is a data frame (and no vector),
-and only selected variables from \code{data} should be processed.
-You may also use functions like \code{:} or tidyselect's
-\code{select_helpers()}.}
-
 \item{method}{Character vector, indicating if confidence intervals should be
 based on bootstrap standard error, multiplied by the value of the
 quantile function of the t-distribution (default), or on sample
@@ -32,6 +26,12 @@ quantiles of the bootstrapped values. See 'Details' in \code{boot_ci()}.
 May be abbreviated.}
 
 \item{ci.lvl}{Numeric, the level of the confidence intervals.}
+
+\item{...}{Optional, unquoted names of variables with bootstrapped estimates.
+Required, if either \code{data} is a data frame (and no vector),
+and only selected variables from \code{data} should be processed.
+You may also use functions like \code{:} or tidyselect's
+\code{select_helpers()}.}
 }
 \value{
 A data frame with either bootstrap estimate,
@@ -79,11 +79,14 @@ data(efc)
 bs <- bootstrap(efc, 100)
 
 # now run models for each bootstrapped sample
-bs$models <- map(bs$strap, ~lm(neg_c_7 ~ e42dep + c161sex, data = .x))
+bs$models <- lapply(
+  bs$strap,
+  function(.x) lm(neg_c_7 ~ e42dep + c161sex, data = .x)
+)
 
 # extract coefficient "dependency" and "gender" from each model
-bs$dependency <- map_dbl(bs$models, ~coef(.x)[2])
-bs$gender <- map_dbl(bs$models, ~coef(.x)[3])
+bs$dependency <- vapply(bs$models, function(x) coef(x)[2], numeric(1))
+bs$gender <- vapply(bs$models, function(x) coef(x)[3], numeric(1))
 
 # get bootstrapped confidence intervals
 boot_ci(bs$dependency)
@@ -94,9 +97,9 @@ confint(fit)[2, ]
 
 # alternative function calls.
 boot_ci(bs$dependency)
-boot_ci(bs, dependency)
-boot_ci(bs, dependency, gender)
-boot_ci(bs, dependency, gender, method = "q")
+boot_ci(bs, "dependency")
+boot_ci(bs, c("dependency", "gender"))
+boot_ci(bs, c("dependency", "gender"), method = "q")
 
 
 # compare coefficients
diff --git a/man/gmd.Rd b/man/gmd.Rd
index 03823df..f8ca77f 100644
--- a/man/gmd.Rd
+++ b/man/gmd.Rd
@@ -4,7 +4,7 @@
 \alias{gmd}
 \title{Gini's Mean Difference}
 \usage{
-gmd(x, ...)
+gmd(x, select = NULL)
 }
 \arguments{
 \item{x}{A vector or data frame.}
@@ -30,7 +30,7 @@ silently removed.
 \examples{
 data(efc)
 gmd(efc$e17age)
-gmd(efc, e17age, c160age, c12hour)
+gmd(efc, c("e17age", "c160age", "c12hour"))
 
 }
 \references{