Last updated on 2025-12-06 00:48:57 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.7.1 | 3.40 | 135.15 | 138.55 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.7.1 | 3.01 | 43.90 | 46.91 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.7.1 | 211.35 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 0.7.1 | 217.63 | OK | |||
| r-devel-windows-x86_64 | 0.7.1 | 9.00 | 142.00 | 151.00 | OK | |
| r-patched-linux-x86_64 | 0.7.1 | 4.54 | 124.37 | 128.91 | OK | |
| r-release-linux-x86_64 | 0.7.1 | 4.01 | 128.13 | 132.14 | OK | |
| r-release-macos-arm64 | 0.7.1 | OK | ||||
| r-release-macos-x86_64 | 0.7.1 | 3.00 | 130.00 | 133.00 | OK | |
| r-release-windows-x86_64 | 0.7.1 | 6.00 | 140.00 | 146.00 | OK | |
| r-oldrel-macos-arm64 | 0.7.1 | OK | ||||
| r-oldrel-macos-x86_64 | 0.7.1 | 3.00 | 120.00 | 123.00 | OK | |
| r-oldrel-windows-x86_64 | 0.7.1 | 8.00 | 173.00 | 181.00 | OK |
Version: 0.7.1
Check: package dependencies
Result: WARN
Cannot process vignettes
Packages suggested but not available for checking:
'gt', 'knitr', 'rmarkdown'
VignetteBuilder package required for checking but not installed: ‘knitr’
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.7.1
Check: examples
Result: ERROR
Running examples in ‘rifttable-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: rifttable
> ### Title: Results Tables for Epidemiology
> ### Aliases: rifttable
>
> ### ** Examples
>
> # Load 'cancer' dataset from survival package (Used in all examples)
> data(cancer, package = "survival")
>
> # The exposure (here, 'sex') must be categorical
> cancer <- cancer |>
+ tibble::as_tibble() |>
+ dplyr::mutate(
+ sex = factor(
+ sex,
+ levels = 1:2,
+ labels = c("Male", "Female")
+ ),
+ time = time / 365.25,
+ status = status - 1
+ )
>
>
> # Example 1: Binary outcomes (use 'outcome' variable)
> # Set table design
> design1 <- tibble::tibble(
+ label = c(
+ "Outcomes",
+ "Total",
+ "Outcomes/Total",
+ "Risk",
+ "Risk (CI)",
+ "Outcomes (Risk)",
+ "Outcomes/Total (Risk)",
+ "RR",
+ "RD"
+ )
+ ) |>
+ dplyr::mutate(
+ type = label,
+ exposure = "sex",
+ outcome = "status"
+ )
>
> # Generate rifttable
> rifttable(
+ design = design1,
+ data = cancer
+ )
# A tibble: 9 × 3
sex Male Female
<chr> <chr> <chr>
1 Outcomes 112 53
2 Total 138 90
3 Outcomes/Total 112/138 53/90
4 Risk 0.81 0.59
5 Risk (CI) 0.81 (0.74, 0.87) 0.59 (0.49, 0.68)
6 Outcomes (Risk) 112 (0.81) 53 (0.59)
7 Outcomes/Total (Risk) 112/138 (0.81) 53/90 (0.59)
8 RR 1 (reference) 0.73 (0.60, 0.88)
9 RD 0 (reference) -0.22 (-0.34, -0.10)
>
> # Use 'design' as columns (selecting RR and RD only)
> rifttable(
+ design = design1 |>
+ dplyr::filter(label %in% c("RR", "RD")),
+ data = cancer,
+ layout = "cols"
+ )
# A tibble: 2 × 3
sex RR RD
<chr> <chr> <chr>
1 Male 1 (reference) 0 (reference)
2 Female 0.73 (0.60, 0.88) -0.22 (-0.34, -0.10)
>
>
> # Example 2: Survival outcomes (use 'time' and 'event'),
> # with an effect modifier and a confounder
> # Set table design
> design2 <- tibble::tribble(
+ # Elements that vary by row:
+ ~label, ~stratum, ~confounders, ~type,
+ "**Overall**", NULL, "", "blank",
+ " Events", NULL, "", "events",
+ " Person-years", NULL, "", "time",
+ " Rate/1000 py (95% CI)", NULL, "", "rate (ci)",
+ " Unadjusted HR (95% CI)", NULL, "", "hr",
+ " Age-adjusted HR (95% CI)", NULL, "+ age", "hr",
+ "", NULL, "", "blank",
+ "**Stratified models**", NULL, "", "",
+ "*ECOG PS1* (events/N)", 1, "", "events/total",
+ " Unadjusted", 1, "", "hr",
+ " Age-adjusted", 1, "+ age", "hr",
+ "*ECOG PS2* (events/N)", 2, "", "events/total",
+ " Unadjusted", 2, "", "hr",
+ " Age-adjusted", 2, "+ age", "hr",
+ "", NULL, "", "",
+ "**Joint model**, age-adj.", NULL, "", "",
+ " ECOG PS1", 1, "+ age", "hr_joint",
+ " ECOG PS2", 2, "+ age", "hr_joint"
+ ) |>
+ # Elements that are the same for all rows:
+ dplyr::mutate(
+ exposure = "sex",
+ event = "status",
+ time = "time",
+ effect_modifier = "ph.ecog"
+ )
>
> # Generate rifttable
> rifttable(
+ design = design2,
+ data = cancer |>
+ dplyr::filter(ph.ecog %in% 1:2)
+ )
# A tibble: 18 × 3
sex Male Female
<chr> <chr> <chr>
1 "**Overall**" "" ""
2 " Events" "82" "44"
3 " Person-years" "70" "59"
4 " Rate/1000 py (95% CI)" "1164.8 (938.1, 1446.3)" "746.7 (555.7, 1003.4)"
5 " Unadjusted HR (95% CI)" "1 (reference)" "0.60 (0.41, 0.86)"
6 " Age-adjusted HR (95% CI)" "1 (reference)" "0.60 (0.41, 0.86)"
7 "" "" ""
8 "**Stratified models**" "" ""
9 "*ECOG PS1* (events/N)" "54/71" "28/42"
10 " Unadjusted" "1 (reference)" "0.53 (0.33, 0.85)"
11 " Age-adjusted" "1 (reference)" "0.53 (0.33, 0.85)"
12 "*ECOG PS2* (events/N)" "28/29" "16/21"
13 " Unadjusted" "1 (reference)" "0.70 (0.37, 1.30)"
14 " Age-adjusted" "1 (reference)" "0.68 (0.34, 1.36)"
15 "" "" ""
16 "**Joint model**, age-adj." "" ""
17 " ECOG PS1" "1 (reference)" "0.55 (0.35, 0.88)"
18 " ECOG PS2" "1.54 (0.98, 2.44)" "1.10 (0.62, 1.98)"
>
>
> # Example 3: Get two estimates using 'type' and 'type2'
> design3 <- tibble::tribble(
+ ~label, ~stratum, ~type, ~type2,
+ "ECOG PS1", 1, "events/total", "hr",
+ "ECOG PS2", 2, "events/total", "hr"
+ ) |>
+ dplyr::mutate(
+ exposure = "sex",
+ event = "status",
+ time = "time",
+ confounders = "+ age",
+ effect_modifier = "ph.ecog"
+ )
>
> rifttable(
+ design = design3,
+ data = cancer |>
+ dplyr::filter(ph.ecog %in% 1:2)
+ )
# A tibble: 4 × 3
sex Male Female
<chr> <chr> <chr>
1 "ECOG PS1" 54/71 28/42
2 "" 1 (reference) 0.53 (0.33, 0.85)
3 "ECOG PS2" 28/29 16/21
4 "" 1 (reference) 0.68 (0.34, 1.36)
>
> rifttable(
+ design = design3,
+ data = cancer |>
+ dplyr::filter(ph.ecog %in% 1:2),
+ layout = "cols",
+ type2_layout = "cols"
+ )
# A tibble: 2 × 5
sex `ECOG PS1` `ECOG PS1 ` `ECOG PS2` `ECOG PS2 `
<chr> <chr> <chr> <chr> <chr>
1 Male 54/71 1 (reference) 28/29 1 (reference)
2 Female 28/42 0.53 (0.33, 0.85) 16/21 0.68 (0.34, 1.36)
>
>
> # Example 4: Continuous outcomes (use 'outcome' variable);
> # request rounding to 1 decimal digit in some cases;
> # add continuous trend (slope per one unit of the 'trend' variable)
> tibble::tribble(
+ ~label, ~stratum, ~type, ~digits,
+ "Marginal mean (95% CI)", NULL, "mean (ci)", 1,
+ " Male", "Male", "mean", NA,
+ " Female", "Female", "mean", NA,
+ "", NULL, "", NA,
+ "Stratified model", NULL, "", NA,
+ " Male", "Male", "diff", 1,
+ " Female", "Female", "diff", 1,
+ "", NULL, "", NA,
+ "Joint model", NULL, "", NA,
+ " Male", "Male", "diff_joint", NA,
+ " Female", "Female", "diff_joint", NA
+ ) |>
+ dplyr::mutate(
+ exposure = "ph.ecog_factor",
+ trend = "ph.ecog",
+ outcome = "age",
+ effect_modifier = "sex"
+ ) |>
+ rifttable(
+ data = cancer |>
+ dplyr::filter(ph.ecog < 3) |>
+ dplyr::mutate(ph.ecog_factor = factor(ph.ecog))
+ )
# A tibble: 11 × 5
ph.ecog_factor `0` `1` `2` Trend
<chr> <chr> <chr> <chr> <chr>
1 "Marginal mean (95% CI)" "61.2 (58.8, 63.5)" "61.5 (59.8, 63.1… "66.… ""
2 " Male" "63.00" "62.79" "65.… ""
3 " Female" "58.70" "59.19" "67.… ""
4 "" "" "" "" ""
5 "Stratified model" "" "" "" ""
6 " Male" "0 (reference)" "-0.2 (-3.9, 3.5)" "2.0… "0.9…
7 " Female" "0 (reference)" "0.5 (-3.5, 4.5)" "9.2… "4.4…
8 "" "" "" "" ""
9 "Joint model" "" "" "" ""
10 " Male" "0 (reference)" "-0.21 (-3.75, 3.… "2.0… "0.9…
11 " Female" "-4.30 (-8.70, 0.11)" "-3.81 (-7.74, 0.… "4.9… "4.3…
>
>
> # Example 5: Get formatted output for Example 2
> rifttable(
+ design = design2,
+ data = cancer |>
+ dplyr::filter(ph.ecog %in% 1:2)
+ ) |>
+ rt_gt()
Error in loadNamespace(x) : there is no package called ‘knitr’
Calls: rt_gt ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.7.1
Check: package vignettes
Result: NOTE
Package has ‘vignettes’ subdirectory but apparently no vignettes.
Perhaps the ‘VignetteBuilder’ information is missing from the
DESCRIPTION file?
Flavor: r-devel-linux-x86_64-debian-gcc