Tidy Roxygen documentation (newlines & bullet lists)

DESCRIPTION

@@ -43,7 +43,7 @@ Imports:
     rlang,
     scales,
     stats,
-    survival (>= 3.1-11),
+    survival (>= 3.2-13),
     tibble,
     tidyr,
     utils

R/abnormal.R

@@ -2,13 +2,13 @@
 #'
 #' @description `r lifecycle::badge("stable")`
 #'
-#' Primary analysis variable `.var` indicates the abnormal range result (character or factor)
-#' and additional analysis variables are `id` (character or factor) and `baseline` (character or
-#' factor). For each direction specified in `abnormal` (e.g. high or low) count patients in the
+#' Primary analysis variable `.var` indicates the abnormal range result (`character` or `factor`)
+#' and additional analysis variables are `id` (`character` or `factor`) and `baseline` (`character` or
+#' `factor`). For each direction specified in `abnormal` (e.g. high or low) count patients in the
 #' numerator and denominator as follows:
 #' \describe{
-#'   \item{`num`}{the number of patients with this abnormality recorded while on treatment.}
-#'   \item{`denom`}{the number of patients with at least one post-baseline assessment.}
+#'   \item{num}{the number of patients with this abnormality recorded while on treatment.}
+#'   \item{denom}{the number of patients with at least one post-baseline assessment.}
 #' }
 #' Note, the denominator includes patients that might have other abnormal levels at baseline,
 #' and patients with missing baseline. Note, optionally patients with this abnormality at
@@ -23,7 +23,6 @@
 #'
 #' @name abnormal
 #' @include formats.R
-#'
 NULL
 
 #' @describeIn abnormal Statistics function which counts patients with abnormal range values

R/abnormal_by_baseline.R

@@ -6,18 +6,18 @@
 #' Note that `df` should be filtered to include only post-baseline records.
 #'
 #' Primary analysis variable `.var` indicates the abnormal range result (character or factor), and additional
-#'   analysis variables are `id` (character or factor) and `baseline` (character or factor). For each
-#'   direction specified in `abnormal` (e.g. high or low) we condition on baseline range result and count
-#'   patients in the numerator and denominator as follows:
-#' * `Not <abnormal>`
-#'   * `denom`: the number of patients without abnormality at baseline (excluding those with missing baseline)
-#'   * `num`:  the number of patients in `denom` who also have at least one abnormality post-baseline
-#' * `<Abnormal>`
-#'   * `denom`: the number of patients with abnormality at baseline
-#'   * `num`: the number of patients in `denom` who also have at least one abnormality post-baseline
-#' * `Total`
-#'   * `denom`: the number of patients with at least one valid measurement post-baseline
-#'   * `num`: the number of patients in `denom` who also have at least one abnormality post-baseline
+#' analysis variables are `id` (character or factor) and `baseline` (character or factor). For each
+#' direction specified in `abnormal` (e.g. high or low) we condition on baseline range result and count
+#' patients in the numerator and denominator as follows:
+#'   * `Not <Abnormal>`
+#'     * `denom`: the number of patients without abnormality at baseline (excluding those with missing baseline)
+#'     * `num`:  the number of patients in `denom` who also have at least one abnormality post-baseline
+#'   * `<Abnormal>`
+#'     * `denom`: the number of patients with abnormality at baseline
+#'     * `num`: the number of patients in `denom` who also have at least one abnormality post-baseline
+#'   * `Total`
+#'     * `denom`: the number of patients with at least one valid measurement post-baseline
+#'     * `num`: the number of patients in `denom` who also have at least one abnormality post-baseline
 #'
 #' @inheritParams argument_convention
 #' @param abnormal (`character`)\cr identifying the abnormal range level(s) in `.var`.
@@ -58,7 +58,7 @@ d_count_abnormal_by_baseline <- function(abnormal) {
 #'   Please note that if the baseline variable or analysis variable contains `NA`, it is expected that `NA` has been
 #'   conveyed to `na_level` appropriately beforehand with `df_explicit_na()` or `explicit_na()`.
 #'
-#' @param na_level (`string`) \cr the explicit `na_level` argument you used in the pre-processing steps (maybe with
+#' @param na_level (`string`)\cr the explicit `na_level` argument you used in the pre-processing steps (maybe with
 #'   `df_explicit_na()`). The default is `"<Missing>"`.
 #'
 #' @examples
@@ -140,6 +140,7 @@ s_count_abnormal_by_baseline <- function(df,
 
 #' @describeIn abnormal_by_baseline Formatted Analysis function which can be further customized by calling
 #'   [rtables::make_afun()] on it. It is used as `afun` in [rtables::analyze()].
+#'
 #' @return [a_count_abnormal_by_baseline()] returns the corresponding list with formatted [rtables::CellValue()].
 #'
 #' @examples
@@ -163,7 +164,6 @@ a_count_abnormal_by_baseline <- make_afun(
 #' @inheritParams argument_convention
 #'
 #' @examples
-#'
 #' # Layout creating function.
 #' basic_table() %>%
 #'   count_abnormal_by_baseline(var = "ANRIND", abnormal = c(High = "HIGH")) %>%

R/abnormal_by_marked.R

@@ -1,4 +1,4 @@
-#' Count patients with marked laboratory abnormalities
+#' Count Patients with Marked Laboratory Abnormalities
 #'
 #' @description `r lifecycle::badge("stable")`
 #'
@@ -7,27 +7,28 @@
 #' Additional analysis variables are `id` (character or factor) and `direction` indicating
 #' the direction of the abnormality (factor).
 #' Denominator is number of patients with at least one valid measurement during
-#' treatment (post-baseline), and patients in the numerator are considered as follows:
-#' * For `Single, not last` and `Last or replicated`: Numerator is number of patients
-#'   with `Single, not last` and `Last or replicated` levels, respectively.
-#' * For `Any`: Numerator is the number of patients with either single or
-#'   replicated marked abnormalities.
+#'   * For `Single, not last` and `Last or replicated`: Numerator is number of patients
+#'     with `Single, not last` and `Last or replicated` levels, respectively.
+#'   * For `Any`: Numerator is the number of patients with either single or
+#'     replicated marked abnormalities.
 #'
 #' @details Note that `Single, not last` and `Last or replicated` levels are
 #' mutually exclusive. If a patient has abnormalities that meet both the `Single, not last`
 #' and `Last or replicated` criteria, then the patient will be counted only under the `Last or replicated` category.
-
+#'
 #' @inheritParams argument_convention
 #' @param category (`list`)\cr with different marked category names for single
-#' and last or replicated.
-#' @name abnormal_by_marked
+#'   and last or replicated.
 #'
+#' @name abnormal_by_marked
 NULL
+
 #' @describeIn abnormal_by_marked Statistics function which returns
-#' the counts and fractions of patients with `Single, not last`, `Last or replicated` and `Any`
-#' marked laboratory abnormalities for a single `abnormal` level.
+#'   the counts and fractions of patients with `Single, not last`, `Last or replicated` and `Any`
+#'   marked laboratory abnormalities for a single `abnormal` level.
+#'
 #' @return [s_count_abnormal_by_marked()] the single statistic `count_fraction`
-#' with `Single, not last`, `Last or replicated` and `Any` results.
+#'   with `Single, not last`, `Last or replicated` and `Any` results.
 #'
 #' @examples
 #' library(dplyr)
@@ -157,7 +158,7 @@ a_count_abnormal_by_marked <- make_afun(
 )
 
 #' @describeIn abnormal_by_marked Layout creating function which can be used for creating tables,
-#' which can take statistics function arguments and additional format arguments (see below).
+#'   which can take statistics function arguments and additional format arguments (see below).
 #'
 #' @examples
 #' map <- unique(

R/abnormal_by_worst_grade.R

@@ -8,27 +8,27 @@
 #' For a certain direction (e.g. high or low) this function counts
 #' patients in the denominator as number of patients with at least one valid measurement during treatment,
 #' and patients in the numerator as follows:
-#'  * `1` to `4`: Numerator is number of patients with worst grades 1-4 respectively;
-#'  * `Any`: Numerator is number of patients with at least one abnormality, which means grade is different from 0.
+#'   * `1` to `4`: Numerator is number of patients with worst grades 1-4 respectively;
+#'   * `Any`: Numerator is number of patients with at least one abnormality, which means grade is different from 0.
 #'
 #' @details
 #' The pre-processing steps are crucial when using this function. From the standard
 #' lab grade variable `ATOXGR`, derive the following two variables:
-#' * A grade direction variable (e.g. `GRADE_DIR`) is required in order to obtain
-#'   the correct denominators when building the layout as it is used to define row splitting.
-#' * A toxicity grade variable (e.g. `GRADE_ANL`) where all negative values from
-#'   `ATOXGR` are replaced by their absolute values.
-#' * Prior to tabulation, `df` must filtered to include only post-baseline records with worst grade flags.
+#'   * A grade direction variable (e.g. `GRADE_DIR`) is required in order to obtain
+#'     the correct denominators when building the layout as it is used to define row splitting.
+#'   * A toxicity grade variable (e.g. `GRADE_ANL`) where all negative values from
+#'     `ATOXGR` are replaced by their absolute values.
+#'   * Prior to tabulation, `df` must filtered to include only post-baseline records with worst grade flags.
 #'
 #' @inheritParams argument_convention
 #'
 #' @name abnormal_by_worst_grade
-#'
 NULL
 
 #' @describeIn abnormal_by_worst_grade Statistics function which counts patients with worst grade,
 #'   consisting of counts and percentages of patients with worst grade
 #'   `1` to `4`, and `Any` non-zero grade.
+#'
 #' @return [s_count_abnormal_by_worst_grade()] the single statistic `count_fraction` with grade 1 to 4
 #'   and "Any" results.
 #'

R/abnormal_by_worst_grade_worsen.R

@@ -17,25 +17,22 @@ NULL
 #'
 #' Helper function to prepare a `df` for generate the patient count shift table
 #'
-#' @param adlb (`data frame`) \cr `ADLB` dataframe
-#' @param worst_flag_low (named `vector`) \cr
-#' Worst low post-baseline lab grade flag variable
-#' @param worst_flag_high (named `vector`) \cr
-#' Worst high post-baseline lab grade flag variable
-#' @param direction_var (`string`) \cr
-#' Direction variable specifying the direction of the shift table of interest.
-#' Only lab records flagged by `L`, `H` or `B` are included in the shift table.
-#'  * `L`: low direction only
-#'  * `H`: high direction only
-#'  * `B`: both low and high directions
+#' @param adlb (`data.frame`)\cr `ADLB` dataframe
+#' @param worst_flag_low (named `vector`)\cr Worst low post-baseline lab grade flag variable
+#' @param worst_flag_high (named `vector`)\cr Worst high post-baseline lab grade flag variable
+#' @param direction_var (`string`)\cr Direction variable specifying the direction of the shift table of interest.
+#'   Only lab records flagged by `L`, `H` or `B` are included in the shift table.
+#'   * `L`: low direction only
+#'   * `H`: high direction only
+#'   * `B`: both low and high directions
 #'
-#' @return [h_adlb_worsen()] returns the `adlb` `data frame` containing only the
-#' worst labs specified according to `worst_flag_low` or `worst_flag_high` for the
-#' direction specified according to `direction_var`. For instance, for a lab that is
-#' needed for the low direction only, only records flagged by `worst_flag_low` are
-#' selected. For a lab that is needed for both low and high directions, the worst
-#' low records are selected for the low direction, and the worst high record are selected
-#' for the high direction.
+#' @return [h_adlb_worsen()] returns the `adlb` `data.frame` containing only the
+#'   worst labs specified according to `worst_flag_low` or `worst_flag_high` for the
+#'   direction specified according to `direction_var`. For instance, for a lab that is
+#'   needed for the low direction only, only records flagged by `worst_flag_low` are
+#'   selected. For a lab that is needed for both low and high directions, the worst
+#'   low records are selected for the low direction, and the worst high record are selected
+#'   for the high direction.
 #' @seealso [abnormal_by_worst_grade_worsen]
 #'
 #' @examples
@@ -159,10 +156,10 @@ h_adlb_worsen <- function(adlb,
 #'
 #' @inheritParams argument_convention
 #' @inheritParams h_adlb_worsen
-#' @param baseline_var (`string`) \cr baseline lab grade variable
+#' @param baseline_var (`string`)\cr baseline lab grade variable
 #' @return [h_worsen_counter()] returns the counts and fraction of patients
-#' whose worst post-baseline lab grades are worse than their baseline grades, for
-#' post-baseline worst grades "1", "2", "3", "4" and "Any".
+#'   whose worst post-baseline lab grades are worse than their baseline grades, for
+#'   post-baseline worst grades "1", "2", "3", "4" and "Any".
 #' @seealso [abnormal_by_worst_grade_worsen]
 #'
 #' @examples
@@ -261,16 +258,16 @@ h_worsen_counter <- function(df, id, .var, baseline_var, direction_var) {
 }
 
 #' @describeIn abnormal_by_worst_grade_worsen Statistics function which calculates the
-#' counts and fraction of patients whose worst post-baseline lab grades are worse than
-#' their baseline grades, for post-baseline worst grades "1", "2", "3", "4" and "Any".
+#'   counts and fraction of patients whose worst post-baseline lab grades are worse than
+#'   their baseline grades, for post-baseline worst grades "1", "2", "3", "4" and "Any".
 #'
-#' @param variables (named `list` of `string`) \cr list of additional analysis variables including:
-#' * `id` (`string`): \cr subject variable name
-#' * `baseline_var` (`string`): \cr name of the data column containing baseline toxicity variable
-#' * `direction_var` (`string`): See `direction_var` for more detail
+#' @param variables (named `list` of `string`)\cr list of additional analysis variables including:
+#'   * `id` (`string`)\cr subject variable name.
+#'   * `baseline_var` (`string`)\cr name of the data column containing baseline toxicity variable.
+#'   * `direction_var` (`string`)\cr see `direction_var` for more details.
 #' @return [s_count_abnormal_lab_worsen_by_baseline()] returns the
-#' counts and fraction of patients whose worst post-baseline lab grades are worse than
-#' their baseline grades, for post-baseline worst grades "1", "2", "3", "4" and "Any".
+#'   counts and fraction of patients whose worst post-baseline lab grades are worse than
+#'   their baseline grades, for post-baseline worst grades "1", "2", "3", "4" and "Any".
 #'
 #' @examples
 #' library(dplyr)
@@ -327,10 +324,9 @@ s_count_abnormal_lab_worsen_by_baseline <- function(df, # nolint
 
 
 #' @describeIn abnormal_by_worst_grade_worsen
-#' Formatted Analysis function which can be further customized by
-#' calling [rtables::make_afun()] on it. It is used as `afun` in [rtables::analyze()].
-#' @return [a_count_abnormal_lab_worsen_by_baseline()] returns
-#' the corresponding list with formatted [rtables::CellValue()].
+#'
+#' @return [a_count_abnormal_lab_worsen_by_baseline()] returns the corresponding list with
+#'   formatted [rtables::CellValue()].
 #'
 #' @examples
 #' # Internal function - a_count_abnormal_lab_worsen_by_baseline
@@ -349,9 +345,8 @@ a_count_abnormal_lab_worsen_by_baseline <- make_afun( # nolint
   .ungroup_stats = "fraction"
 )
 
-#' @describeIn abnormal_by_worst_grade_worsen Layout
-#' creating function which can be used for creating tables, which can take statistics
-#' function arguments and additional format arguments (see below).
+#' @describeIn abnormal_by_worst_grade_worsen Layout creating function which can be used for creating tables,
+#'   which can take statistics function arguments and additional format arguments (see below).
 #'
 #' @examples
 #' basic_table() %>%

R/analyze_vars_in_cols.R

@@ -15,7 +15,7 @@ NULL
 #' @inheritParams argument_convention
 #' @inheritParams rtables::analyze_colvars
 #'
-#' @seealso [summarize_vars], [rtables::analyze_colvars].
+#' @seealso [summarize_vars], [`rtables::analyze_colvars()`].
 #'
 #' @export
 #' @examples

R/argument_convention.R

@@ -10,30 +10,30 @@
 #' `@inheritParams argument_convention`
 #'
 #' @param ... additional arguments for the lower level functions.
-#' @param .df_row (`data frame`)\cr data frame across all of the columns for the given row split.
+#' @param .df_row (`data.frame`)\cr data frame across all of the columns for the given row split.
 #' @param .in_ref_col (`logical`)\cr `TRUE` when working with the reference level, `FALSE` otherwise.
 #' @param .N_col (`count`)\cr row-wise N (row group count) for the group of observations being analyzed
 #'   (i.e. with no column-based subsetting) that is passed by `rtables`.
 #' @param .N_row (`count`)\cr column-wise N (column count) for the full column that is passed by `rtables`.
-#' @param .ref_group (`data frame` or `vector`)\cr the data corresponding to the reference group.
+#' @param .ref_group (`data.frame` or `vector`)\cr the data corresponding to the reference group.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #' @param .indent_mods (named `integer`)\cr indent modifiers for the labels.
 #' @param .formats (named `character` or `list`)\cr formats for the statistics.
 #' @param .labels (named `character`)\cr labels for the statistics (without indent).
 #' @param .var (`string`)\cr single variable name that is passed by `rtables` when requested
 #'   by a statistics function.
-#' @param .spl_context (`data frame`)\cr gives information about ancestor split states
+#' @param .spl_context (`data.frame`)\cr gives information about ancestor split states
 #'   that is passed by `rtables`.
 #' @param col_by (`factor`)\cr defining column groups.
 #' @param conf_level (`proportion`)\cr confidence level of the interval.
 #' @param data (`data.frame`)\cr the dataset containing the variables to summarize.
-#' @param df (`data frame`)\cr data set containing all analysis variables.
+#' @param df (`data.frame`)\cr data set containing all analysis variables.
 #' @param draw (`flag`)\cr whether the plot should be drawn.
 #' @param drop (`flag`)\cr should non appearing occurrence levels be dropped from the resulting table.
 #'   Note that in that case the remaining occurrence levels in the table are sorted alphabetically.
-#' @param id (`string`) \cr subject variable name.
+#' @param id (`string`)\cr subject variable name.
 #' @param is_event (`logical`)\cr `TRUE` if event, `FALSE` if time to event is censored.
-#' @param indent_mod (`count`) \cr it can be negative. Modifier for the default indent position for the
+#' @param indent_mod (`count`)\cr it can be negative. Modifier for the default indent position for the
 #'   structure created by this function(subtable, content table, or row) and
 #'   all of that structure's children. Defaults to 0, which corresponds to the
 #'   unmodified default behavior.

R/compare_variables.R

@@ -33,8 +33,8 @@ s_compare <- function(x,
 #' @describeIn compare_variables Method for numeric class. This uses the standard t-test
 #'   to calculate the p-value.
 #' @return If `x` is of class `numeric`, returns a list with named items:
-#' - all items from [s_summary.numeric()].
-#' - `pval`: the p-value.
+#'   - all items from [s_summary.numeric()].
+#'   - `pval`: the p-value.
 #' @method s_compare numeric
 #'
 #' @export
@@ -77,8 +77,7 @@ s_compare.numeric <- function(x,
 #'   missing values should be accounted for explicitly as factor levels.
 #' @param denom (`string`)\cr choice of denominator for factor proportions,
 #'   can only be `n` (number of values in this row and column intersection).
-#' @return If `x` is of class `factor` or converted from `character`, returns a list with
-#'   named items:
+#' @return If `x` is of class `factor` or converted from `character`, returns a list with named items:
 #'   - all items from [s_summary.factor()].
 #'   - `pval`: the p-value.
 #' @method s_compare factor