diff --git a/R/boot_ci.R b/R/boot_ci.R
index 5b347838..eb16299d 100644
--- a/R/boot_ci.R
+++ b/R/boot_ci.R
@@ -3,13 +3,18 @@
 #' This function first applies [boot::boot()] to convert the input data `x` to a `boot` object and then uses
 #' [boot::boot.ci()] to calculate the corresponding nonparametric bootstrap confidence interval.
 #'
-#' @param x vector of numeric values, i.e. a numeric vector, or a logical vector which will be interpreted
-#'   as binary with values `c(0, 1)`.
-#' @param conf.level (`numeric`)\cr
-#'   a scalar in `(0, 1)` indicating the confidence level.
-#'   Default is `0.95`
-#' @inheritParams boot::boot
-#' @inheritParams boot::boot.ci
+#' @param x (`numeric`)\cr vector of numeric values, i.e. a numeric vector, or a logical vector which will be
+#'   interpreted as binary with values `c(0, 1)`.
+#' @param conf.level (`numeric`)\cr a scalar in `(0, 1)` indicating the confidence level. Default is `0.95`.
+#' @param R (`integer`)\cr the number of bootstrap replicates. See the parameter description in [boot::boot()]
+#'   for details.
+#' @param type (`character`)\cr a vector of character strings representing the type of intervals required. The value
+#'   should be any subset of the values `c("norm","basic", "stud", "perc", "bca")` or simply `"all"` which will
+#'   compute all five types of intervals.
+#' @param stype (`string`)\cr a character string indicating what the second argument of statistic represents.
+#'   Possible values of stype are `"i"` (indices - the default), `"f"` (frequencies), or `"w"` (weights).
+#' @param statistic (`function`)\cr a function which, when applied to data, returns a vector containing the
+#'   statistic(s) of interest. See the parameter description in [boot::boot()] for details.
 #'
 #' @return Bootstrap confidence interval.
 #' @export
diff --git a/man/boot_ci.Rd b/man/boot_ci.Rd
index 096b21b6..f75a8e37 100644
--- a/man/boot_ci.Rd
+++ b/man/boot_ci.Rd
@@ -14,50 +14,23 @@ boot_ci(
 )
 }
 \arguments{
-\item{x}{vector of numeric values, i.e. a numeric vector, or a logical vector which will be interpreted
-as binary with values \code{c(0, 1)}.}
+\item{x}{(\code{numeric})\cr vector of numeric values, i.e. a numeric vector, or a logical vector which will be
+interpreted as binary with values \code{c(0, 1)}.}
 
-\item{conf.level}{(\code{numeric})\cr
-a scalar in \verb{(0, 1)} indicating the confidence level.
-Default is \code{0.95}}
+\item{conf.level}{(\code{numeric})\cr a scalar in \verb{(0, 1)} indicating the confidence level. Default is \code{0.95}.}
 
-\item{R}{
-    The number of bootstrap replicates.  Usually this will be a single
-    positive integer.  For importance resampling, some resamples may use
-    one set of weights and others use a different set of weights.  In
-    this case \code{R} would be a vector of integers where each
-    component gives the number of resamples from each of the rows of
-    weights.
-  }
+\item{R}{(\code{integer})\cr the number of bootstrap replicates. See the parameter description in \code{\link[boot:boot]{boot::boot()}}
+for details.}
 
-\item{type}{
-    A vector of character strings representing the type of intervals
-    required. The value should be any subset of the values
-    \code{c("norm","basic", "stud", "perc", "bca")} or simply \code{"all"}
-    which will compute all five types of intervals.
-  }
+\item{type}{(\code{character})\cr a vector of character strings representing the type of intervals required. The value
+should be any subset of the values \code{c("norm","basic", "stud", "perc", "bca")} or simply \code{"all"} which will
+compute all five types of intervals.}
 
-\item{stype}{
-    A character string indicating what the second argument of \code{statistic}
-    represents.  Possible values of stype are \code{"i"} (indices - the
-    default), \code{"f"} (frequencies), or \code{"w"} (weights).  Not
-    used for \code{sim = "parametric"}.
-  }
+\item{stype}{(\code{string})\cr a character string indicating what the second argument of statistic represents.
+Possible values of stype are \code{"i"} (indices - the default), \code{"f"} (frequencies), or \code{"w"} (weights).}
 
-\item{statistic}{
-    A function which when applied to data returns a vector containing
-    the statistic(s) of interest.  When \code{sim = "parametric"}, the
-    first argument to \code{statistic} must be the data.  For each
-    replicate a simulated dataset returned by \code{ran.gen} will be
-    passed.  In all other cases \code{statistic} must take at least two
-    arguments.  The first argument passed will always be the original
-    data.  The second will be a vector of indices, frequencies or weights
-    which define the bootstrap sample.  Further, if predictions are
-    required, then a third argument is required which would be a vector
-    of the random indices used to generate the bootstrap predictions.
-    Any further arguments can be passed to \code{statistic} through the
-    \code{\dots} argument.
-  }
+\item{statistic}{(\code{function})\cr a function which, when applied to data, returns a vector containing the
+statistic(s) of interest. See the parameter description in \code{\link[boot:boot]{boot::boot()}} for details.}
 }
 \value{
 Bootstrap confidence interval.