add sd and var

NAMESPACE

@@ -39,6 +39,8 @@ export(proportion_ci_strat_wilson)
 export(proportion_ci_wald)
 export(proportion_ci_wilson)
 export(single_ci_mean)
+export(single_ci_sd)
+export(single_ci_var)
 export(starts_with)
 export(where)
 import(rlang)

R/ard_single_ci.R

@@ -26,7 +26,7 @@ ard_single_ci <- function(data,
                           variables,
                           by = dplyr::group_vars(data),
                           conf.level = 0.95,
-                          method = c("mean_with_T", "mean_with_Z")) {
+                          method = c("mean_with_T", "mean_with_Z", "sd", "var")) {
   # process inputs -------------------------------------------------------------
   cards::process_selectors(data, variables = {{ variables }}, by = {{ by }})
   method <- arg_match(method)
@@ -41,7 +41,9 @@ ard_single_ci <- function(data,
         single_ci =
           switch(method,
                  "mean_with_T" = \(x, ...) single_ci_mean(x, conf.level = conf.level, use_t = TRUE),
-                 "mean_with_Z" = \(x, ...) single_ci_mean(x, conf.level = conf.level, use_t = FALSE)
+                 "mean_with_Z" = \(x, ...) single_ci_mean(x, conf.level = conf.level, use_t = FALSE),
+                 "sd" = \(x, ...) single_ci_sd(x, conf.level = conf.level),
+                 "var"= \(x, ...) single_ci_sd(x, conf.level = conf.level)
           )
       )
   ) |>

R/single_ci.R

@@ -6,7 +6,7 @@
 #' @param conf.level (`numeric`)\cr
 #'   a scalar in `(0, 1)` indicating the confidence level.
 #'   Default is `0.95`
-#' @param use_t (`logicla`)\cr
+#' @param use_t (`logical`)\cr
 #'   a logical to indicated whether to use normal or t distribution.
 #'   Default is t distribution.
 #' @return Confidence interval of a mean
@@ -17,6 +17,8 @@
 #'
 #' single_ci_mean(x, conf.level = 0.9, use_t = TRUE)
 #' single_ci_mean(x, conf.level = 0.9, use_t = FALSE)
+#' single_ci_sd(x, conf.level = 0.9)
+#' single_ci_var(x, conf.level = 0.9)
 NULL
 
 #' @describeIn single_ci Calculates the mean confidenence interval by following
@@ -57,3 +59,68 @@ single_ci_mean  <- function(x, conf.level = 0.95, use_t = TRUE) {
       glue::glue("Mean Confidence Interval {ifelse(use_t, 'with Student t', 'with Normal')} Distribution")
   )
 }
+
+
+#' @describeIn single_ci Calculates the standard deviation confidence interval by following
+#' the usual textbook definition with the chi-sq distribution
+#'
+#' @export
+single_ci_sd  <- function(x, conf.level = 0.95) {
+  # check inputs ---------------------------------------------------------------
+  check_not_missing(x)
+  check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
+  check_scalar_logical(use_t)
+
+  x <- stats::na.omit(x)
+
+  n <- length(x)
+  sd <- sd(x)
+  alpha <- 1 - conf.level
+  crit_value_left <- stats::qchisq(alpha / 2, df = n - 1)
+  crit_value_right <- stats::qchisq((1 - alpha) / 2, df = n - 1)
+
+  l_ci <- sqrt((n - 1) * sd^2 / crit_value_left )
+  u_ci <- sqrt((n - 1) * sd^2 / crit_value_right )
+
+  list(
+    N = n,
+    estimate = sd,
+    conf.low = l_ci,
+    conf.high = u_ci,
+    conf.level = conf.level,
+    method =
+      glue::glue("SD Confidence Interval using chi-sq distribution")
+  )
+}
+
+#' @describeIn single_ci Calculates the variance deviation confidence interval by following
+#' the usual textbook definition with the chi-sq distribution
+#'
+#' @export
+single_ci_var  <- function(x, conf.level = 0.95) {
+  # check inputs ---------------------------------------------------------------
+  check_not_missing(x)
+  check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
+  check_scalar_logical(use_t)
+
+  x <- stats::na.omit(x)
+
+  n <- length(x)
+  var <- var(x)
+  alpha <- 1 - conf.level
+  crit_value_left <- stats::qchisq(alpha / 2, df = n - 1)
+  crit_value_right <- stats::qchisq((1 - alpha) / 2, df = n - 1)
+
+  l_ci <- (n - 1) * var / crit_value_left
+  u_ci <- (n - 1) * var / crit_value_right
+
+  list(
+    N = n,
+    estimate = var,
+    conf.low = l_ci,
+    conf.high = u_ci,
+    conf.level = conf.level,
+    method =
+      glue::glue("Variance Confidence Interval using chi-sq distribution")
+  )
+}