Finetune fixed_design documentation format

R/fixed_design_ahr.R

@@ -16,20 +16,22 @@
 #  You should have received a copy of the GNU General Public License
 #  along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
-#' Fixed design under non-proportional hazards.
+#' Fixed design under non-proportional hazards
 #'
+#' @description
 #' Computes fixed design sample size (given power)
-#' or power (given sample size) by either AHR method
-#' \code{fixed_design_ahr}, weighted logrank test with
-#' Fleming-Harrington weights (Farrington and Manning, 1990)
-#' \code{fixed_design_fh}, weighted logrank test with
-#' Magirr-Burman weights \code{fixed_design_mb},
-#' Lachin-Foulkes method (Lachin and Foulkes, 1986)
-#' \code{fixed_design_lf}, MaxCombo method \code{fixed_design_combo},
-#' RMST method \code{fixed_design_rmst}, or milestone method
-#' \code{fixed_design_milestone}. Additionally, we provide the fixed
-#' design for binary endpoint with treatment effect measuring in
-#' risk difference \code{fixed_design_rd}.
+#' or power (given sample size) by:
+#' - [fixed_design_ahr()] - Average hazard ratio method.
+#' - [fixed_design_fh()] - Weighted logrank test with Fleming-Harrington
+#'   weights (Farrington and Manning, 1990).
+#' - [fixed_design_mb()] - Weighted logrank test with Magirr-Burman weights.
+#' - [fixed_design_lf()] - Lachin-Foulkes method (Lachin and Foulkes, 1986).
+#' - [fixed_design_combo()] - MaxCombo method.
+#' - [fixed_design_rmst()] - RMST method.
+#' - [fixed_design_milestone()] - Milestone method.
+#'
+#' Additionally, [fixed_design_rd()] provides fixed design for binary endpoint
+#' with treatment effect measuring in risk difference.
 #'
 #' @inheritParams gs_design_ahr
 #' @inheritParams gs_power_ahr
@@ -38,13 +40,18 @@
 #' @param study_duration Study duration.
 #'
 #' @importFrom dplyr filter
+#'
 #' @returns A list of design characteristic summary.
+#'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # AHR method ----
 #' library(dplyr)
 #'
-#' # AHR method example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_ahr(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -58,7 +65,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # AHR method example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_ahr(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -72,7 +79,6 @@
 #' )
 #' x %>% summary()
 #'
-#' # ---
 fixed_design_ahr <- function(
     enroll_rate,
     fail_rate,

R/fixed_design_fh.R

@@ -16,7 +16,6 @@
 #  You should have received a copy of the GNU General Public License
 #  along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
-
 #' @inheritParams gs_design_wlr
 #' @inheritParams gs_power_wlr
 #' @param power Power (`NULL` to compute power or strictly between 0
@@ -28,11 +27,14 @@
 #' @importFrom dplyr filter
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # WLR test with FH weights ----
 #' library(dplyr)
 #'
-#' # WLR test with FH weights example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_fh(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -47,7 +49,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # WLR test with FH weights example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_fh(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -62,7 +64,6 @@
 #' )
 #' x %>% summary()
 #'
-#' # ----
 fixed_design_fh <- function(
     alpha = 0.025,
     power = NULL,

R/fixed_design_lf.R

@@ -24,11 +24,14 @@
 #' @inheritParams gs_design_ahr
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # LF method ----
 #' library(dplyr)
 #'
-#' # LF method example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_lf(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -42,7 +45,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # LF method example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_fh(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -56,7 +59,6 @@
 #' )
 #' x %>% summary()
 #'
-#' # ----
 fixed_design_lf <- function(
     alpha = 0.025,
     power = NULL,

R/fixed_design_maxcombo.R

@@ -27,11 +27,14 @@
 #' @inheritParams gs_design_combo
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # MaxCombo test ----
 #' library(dplyr)
 #'
-#' # Maxcombo test example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_maxcombo(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -46,7 +49,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # Maxcombo test example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_maxcombo(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -61,7 +64,6 @@
 #' )
 #' x %>% summary()
 #'
-#' # ----
 fixed_design_maxcombo <- function(
     alpha = 0.025,
     power = NULL,

R/fixed_design_mb.R

@@ -25,11 +25,14 @@
 #' @param tau Test parameter of Magirr-Burman method.
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # WLR test with MB weights ----
 #' library(dplyr)
 #'
-#' # WLR test with MB weights example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_mb(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -44,7 +47,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # WLR test with MB weights example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_mb(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -59,7 +62,6 @@
 #' )
 #' x %>% summary()
 #'
-#' # ----
 fixed_design_mb <- function(
     alpha = 0.025,
     power = NULL,

R/fixed_design_milestone.R

@@ -25,11 +25,14 @@
 #' @param tau Test parameter of milestone method.
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # Milestone method ----
 #' library(dplyr)
 #'
-#' # Milestone method example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_milestone(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -44,7 +47,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # Milestone method example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_milestone(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -59,7 +62,6 @@
 #' )
 #' x %>% summary()
 #'
-#' # ----
 fixed_design_milestone <- function(
     alpha = 0.025,
     power = NULL,

R/fixed_design_rd.R

@@ -27,25 +27,27 @@
 #' @param ratio Experimental:Control randomization ratio.
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # Binary endpoint with risk differences ----
 #' library(dplyr)
 #'
-#' # Binary endpoint with risk differences example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_rd(
 #'   alpha = 0.025, power = 0.9, p_c = .15, p_e = .1,
 #'   rd0 = 0, ratio = 1
 #' )
 #' x %>% summary()
 #'
-#' # Binary endpoint with risk differences example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_rd(
 #'   alpha = 0.025, power = NULL, p_c = .15, p_e = .1,
 #'   rd0 = 0, n = 2000, ratio = 1
 #' )
 #' x %>% summary()
 #'
-#' # ----
 fixed_design_rd <- function(
     alpha = 0.025,
     power = NULL,

R/fixed_design_rmst.R

@@ -25,11 +25,14 @@
 #' @param tau Test parameter in RMST.
 #'
 #' @export
+#'
 #' @rdname fixed_design
+#'
 #' @examples
+#' # RMST method ----
 #' library(dplyr)
 #'
-#' # RMST method example 1: given power and compute sample size
+#' # Example 1: given power and compute sample size
 #' x <- fixed_design_rmst(
 #'   alpha = .025, power = .9,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 1),
@@ -44,7 +47,7 @@
 #' )
 #' x %>% summary()
 #'
-#' # RMST method example 2: given sample size and compute power
+#' # Example 2: given sample size and compute power
 #' x <- fixed_design_rmst(
 #'   alpha = .025,
 #'   enroll_rate = define_enroll_rate(duration = 18, rate = 20),
@@ -58,8 +61,6 @@
 #'   tau = 18
 #' )
 #' x %>% summary()
-#'
-#' # ----
 fixed_design_rmst <- function(
     alpha = 0.025,
     power = NULL,