New R version changed default quotes

R/abnormal.R

@@ -25,7 +25,7 @@
 #'   from numerator and denominator.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("abnormal"))``
+#'   Options are: ``r shQuote(get_stats("abnormal"), type = "sh")``
 #'
 #' @note
 #' * `count_abnormal()` only considers a single variable that contains multiple abnormal levels.

R/abnormal_by_baseline.R

@@ -31,7 +31,7 @@
 #' @param abnormal (`character`)\cr values identifying the abnormal range level(s) in `.var`.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("abnormal_by_baseline"))``
+#'   Options are: ``r shQuote(get_stats("abnormal_by_baseline"), type = "sh")``
 #'
 #' @note
 #' * `df` should be filtered to include only post-baseline records.

R/abnormal_by_marked.R

@@ -30,7 +30,7 @@
 #'   and last or replicated.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("abnormal_by_marked"))``
+#'   Options are: ``r shQuote(get_stats("abnormal_by_marked"), type = "sh")``
 #'
 #' @note `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

R/abnormal_by_worst_grade.R

@@ -29,7 +29,7 @@
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("abnormal_by_worst_grade"))``
+#'   Options are: ``r shQuote(get_stats("abnormal_by_worst_grade"), type = "sh")``
 #'
 #' @seealso [h_adlb_abnormal_by_worst_grade()] which pre-processes ADLB data frames to be used in
 #'   [count_abnormal_by_worst_grade()].

R/abnormal_by_worst_grade_worsen.R

@@ -30,7 +30,7 @@
 #'   * `direction_var` (`string`)\cr see `direction_var` for more details.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("abnormal_by_worst_grade_worsen"))``
+#'   Options are: ``r shQuote(get_stats("abnormal_by_worst_grade_worsen"), type = "sh")``
 #'
 #' @seealso Relevant helper functions [h_adlb_worsen()] and [h_worsen_counter()] which are used within
 #' [s_count_abnormal_lab_worsen_by_baseline()] to process input data.

R/analyze_variables.R

@@ -61,9 +61,9 @@ control_analyze_vars <- function(conf_level = 0.95,
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options for numeric variables are: ``r shQuote(get_stats("analyze_vars_numeric"))``
+#'   Options for numeric variables are: ``r shQuote(get_stats("analyze_vars_numeric"), type = "sh")``
 #'
-#'   Options for non-numeric variables are: ``r shQuote(get_stats("analyze_vars_counts"))``
+#'   Options for non-numeric variables are: ``r shQuote(get_stats("analyze_vars_counts"), type = "sh")``
 #'
 #' @name analyze_variables
 #' @order 1

R/compare_variables.R

@@ -16,9 +16,9 @@
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options for numeric variables are: ``r shQuote(get_stats("analyze_vars_numeric", add_pval = TRUE))``
+#'   Options for numeric variables are: ``r shQuote(get_stats("analyze_vars_numeric", add_pval = TRUE), type = "sh")``
 #'
-#'   Options for non-numeric variables are: ``r shQuote(get_stats("analyze_vars_counts", add_pval = TRUE))``
+#'   Options for non-numeric variables are: ``r shQuote(get_stats("analyze_vars_counts", add_pval = TRUE), type = "sh")``
 #'
 #' @note
 #' * For factor variables, `denom` for factor proportions can only be `n` since the purpose is to compare proportions

R/count_cumulative.R

@@ -16,7 +16,7 @@
 #' @param thresholds (`numeric`)\cr vector of cutoff values for the counts.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_cumulative"))``
+#'   Options are: ``r shQuote(get_stats("count_cumulative"), type = "sh")``
 #'
 #' @seealso Relevant helper function [h_count_cumulative()], and descriptive function [d_count_cumulative()].
 #'

R/count_missed_doses.R

@@ -14,7 +14,7 @@
 #' @param thresholds (`numeric`)\cr minimum number of missed doses the patients had.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_missed_doses"))``
+#'   Options are: ``r shQuote(get_stats("count_missed_doses"), type = "sh")``
 #'
 #' @seealso
 #' * Relevant description function [d_count_missed_doses()] which generates labels for [count_missed_doses()].

R/count_occurrences.R

@@ -19,7 +19,7 @@
 #'   Note that in that case the remaining occurrence levels in the table are sorted alphabetically.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_occurrences"))``
+#'   Options are: ``r shQuote(get_stats("count_occurrences"), type = "sh")``
 #'
 #' @note By default, occurrences which don't appear in a given row split are dropped from the table and
 #'   the occurrences in the table are sorted alphabetically per row split. Therefore, the corresponding layout

R/count_occurrences_by_grade.R

@@ -27,7 +27,7 @@
 #'   should be displayed (`FALSE`).
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_occurrences_by_grade"))``
+#'   Options are: ``r shQuote(get_stats("count_occurrences_by_grade"), type = "sh")``
 #'
 #' @seealso Relevant helper function [h_append_grade_groups()].
 #'

R/count_patients_events_in_cols.R

@@ -22,7 +22,7 @@
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
 #'   In addition to any statistics added using `filters_list`, statistic options are:
-#'   ``r shQuote(get_stats("summarize_patients_events_in_cols"))``
+#'   ``r shQuote(get_stats("summarize_patients_events_in_cols"), type = "sh")``
 #'
 #' @name count_patients_events_in_cols
 #' @order 1

R/count_patients_with_event.R

@@ -19,7 +19,7 @@
 #'   Note that only equality is being accepted as condition.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_patients_with_event"))``
+#'   Options are: ``r shQuote(get_stats("count_patients_with_event"), type = "sh")``
 #'
 #' @seealso [count_patients_with_flags()]
 #'

R/count_patients_with_flags.R

@@ -18,7 +18,7 @@
 #'   the `.labels` parameter, the `.labels` values will take precedence and replace these labels.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_patients_with_flags"))``
+#'   Options are: ``r shQuote(get_stats("count_patients_with_flags"), type = "sh")``
 #'
 #' @seealso [count_patients_with_event]
 #'

R/count_values.R

@@ -13,7 +13,7 @@
 #' @param values (`character`)\cr specific values that should be counted.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("count_values"))``
+#'   Options are: ``r shQuote(get_stats("count_values"), type = "sh")``
 #'
 #' @note
 #' * For `factor` variables, `s_count_values` checks whether `values` are all included in the levels of `x`

R/estimate_multinomial_rsp.R

@@ -9,7 +9,7 @@
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("estimate_multinomial_response"))``
+#'   Options are: ``r shQuote(get_stats("estimate_multinomial_response"), type = "sh")``
 #'
 #' @seealso Relevant description function [d_onco_rsp_label()].
 #'

R/estimate_proportion.R

@@ -16,7 +16,7 @@
 #' @param long (`flag`)\cr whether a long description is required.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("estimate_proportion"))``
+#'   Options are: ``r shQuote(get_stats("estimate_proportion"), type = "sh")``
 #'
 #' @seealso [h_proportions]
 #'

R/incidence_rate.R

@@ -21,7 +21,7 @@
 #'   Defaults to `"USUBJID"`.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("estimate_incidence_rate"))``
+#'   Options are: ``r shQuote(get_stats("estimate_incidence_rate"), type = "sh")``
 #' @param summarize (`flag`)\cr whether the function should act as an analyze function (`summarize = FALSE`), or a
 #'   summarize function (`summarize = TRUE`). Defaults to `FALSE`.
 #' @param label_fmt (`string`)\cr how labels should be formatted after a row split occurs if `summarize = TRUE`. The

R/odds_ratio.R

@@ -13,7 +13,7 @@
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("estimate_odds_ratio"))``
+#'   Options are: ``r shQuote(get_stats("estimate_odds_ratio"), type = "sh")``
 #' @param method (`string`)\cr whether to use the correct (`"exact"`) calculation in the conditional likelihood or one
 #'   of the approximations. See [survival::clogit()] for details.
 #'

R/prop_diff.R

@@ -14,7 +14,7 @@
 #' @param method (`string`)\cr the method used for the confidence interval estimation.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("estimate_proportion_diff"))``
+#'   Options are: ``r shQuote(get_stats("estimate_proportion_diff"), type = "sh")``
 #'
 #' @seealso [d_proportion_diff()]
 #'

R/prop_diff_test.R

@@ -12,7 +12,7 @@
 #'   to calculate the p-value.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("test_proportion_diff"))``
+#'   Options are: ``r shQuote(get_stats("test_proportion_diff"), type = "sh")``
 #'
 #' @seealso [h_prop_diff_test]
 #'

R/summarize_ancova.R

@@ -19,7 +19,7 @@
 #'   used to select the specific ANCOVA results. if the interaction is not needed, the default option is `FALSE`.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("summarize_ancova"))``
+#'   Options are: ``r shQuote(get_stats("summarize_ancova"), type = "sh")``
 #'
 #' @name summarize_ancova
 #' @order 1

R/summarize_change.R

@@ -14,7 +14,7 @@
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("analyze_vars_numeric"))``
+#'   Options are: ``r shQuote(get_stats("analyze_vars_numeric"), type = "sh")``
 #'
 #' @name summarize_change
 #' @order 1

R/summarize_coxreg.R

@@ -7,7 +7,7 @@
 #' @inheritParams argument_convention
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("summarize_coxreg"))``
+#'   Options are: ``r shQuote(get_stats("summarize_coxreg"), type = "sh")``
 #'
 #' @details Cox models are the most commonly used methods to estimate the magnitude of
 #'   the effect in survival analysis. It assumes proportional hazards: the ratio

R/summarize_glm_count.R

@@ -16,7 +16,7 @@
 #' @param scale (`numeric(1)`)\cr linear scaling factor for rate and confidence intervals. Defaults to `1`.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("summarize_glm_count"))``
+#'   Options are: ``r shQuote(get_stats("summarize_glm_count"), type = "sh")``
 #'
 #' @details
 #' `summarize_glm_count()` uses `s_glm_count()` to calculate the statistics for the table. This

R/summarize_num_patients.R

@@ -21,7 +21,7 @@
 #'   Defaults to `TRUE`.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("summarize_num_patients"))``
+#'   Options are: ``r shQuote(get_stats("summarize_num_patients"), type = "sh")``
 #'
 #' @name summarize_num_patients
 #' @order 1

R/summarize_patients_exposure_in_cols.R

@@ -23,7 +23,7 @@
 #' @param custom_label (`string` or `NULL`)\cr if provided and `labelstr` is empty, this will be used as label.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("analyze_patients_exposure_in_cols"))``
+#'   Options are: ``r shQuote(get_stats("analyze_patients_exposure_in_cols"), type = "sh")``
 #'
 #' @name summarize_patients_exposure_in_cols
 #' @order 1

R/survival_coxph_pairwise.R

@@ -22,7 +22,7 @@
 #'   * `conf_level` (`proportion`)\cr confidence level of the interval for HR.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("coxph_pairwise"))``
+#'   Options are: ``r shQuote(get_stats("coxph_pairwise"), type = "sh")``
 #'
 #' @name survival_coxph_pairwise
 #' @order 1

R/survival_time.R

@@ -21,7 +21,7 @@
 #'   for that statistic's row label.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("surv_time"))``
+#'   Options are: ``r shQuote(get_stats("surv_time"), type = "sh")``
 #'
 #' @examples
 #' library(dplyr)

R/survival_timepoint.R

@@ -26,7 +26,7 @@
 #'   for that statistic's row label.
 #' @param .stats (`character`)\cr statistics to select for the table.
 #'
-#'   Options are: ``r shQuote(get_stats("surv_timepoint"))``
+#'   Options are: ``r shQuote(get_stats("surv_timepoint"), type = "sh")``
 #'
 #' @name survival_timepoint
 #' @order 1