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tests/testthat/_snaps/summarize_num_patients.md
In tern: Create Common TLGs Used in Clinical Trials
s_num_patients works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients works as expected with empty input
Code
res
Output
$unique
[1] 0 0
attr(,"label")
[1] ""
$nonunique
[1] 0
attr(,"label")
[1] ""
$unique_count
[1] 0
attr(,"label")
[1] "(n)"
s_num_patients works as expected with unique_count_suffix = FALSE
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] ""
s_num_patients_content works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
summarize_num_patients works as expected with healthy input
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Number of events 4 4
(n) 3 3
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Code
res
Output
A B
(N=5) (N=4)
————————————————————————————————
Number of events 4 4
Code
res
Output
A B
(N=5) (N=4)
———————————————————
(n) 3 3
s_num_patients count_by works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients count_by with missing works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients count_by with missing case 2 works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 3
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients_content with count_by works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 3
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients_content with count_by case 2 works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients_content with count_by trivial cases, identical to without count_by
Code
res
Output
$unique
[1] 4.0 0.8
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 4
attr(,"label")
[1] "(n)"
summarize_num_patients with count_by works as expected with healthy input
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Number of events 3 3
(n) 3 3
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Code
res
Output
A B
(N=5) (N=4)
————————————————————————————————
Number of events 3 3
Code
res
Output
A B
(N=5) (N=4)
———————————————————
(n) 3 3
summarize_num_patients with count_by different combinations works as expected with healthy input
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Number of events 4 3
(n) 3 3
analyze_num_patients works well for pagination
Code
res
Output
A B A+B
(N=5) (N=4) (N=9)
————————————————————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%) 6 (66.7%)
Number of events 4 4 8
e 1.1
Number of patients with at least one event 2 (40.0%) 2 (50.0%) 4 (44.4%)
Number of events 3 3 6
11 1 (20.0%) 1 (25.0%) 2 (22.2%)
19 0 1 (25.0%) 1 (11.1%)
10 1 (20.0%) 0 1 (11.1%)
17 1 (20.0%) 0 1 (11.1%)
f 1.1
Number of patients with at least one event 1 (20.0%) 1 (25.0%) 2 (22.2%)
Number of events 1 1 2
17 0 1 (25.0%) 1 (11.1%)
15 1 (20.0%) 0 1 (11.1%)
summarize_num_patients works as expected with risk difference column
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
cl D
Number of patients with at least one event 40 (19.8%) 40 (22.6%) 29 (17.9%) -2.8 (-11.1 - 5.5)
cl C
Number of patients with at least one event 31 (15.3%) 23 (13.0%) 25 (15.4%) 2.4 (-4.7 - 9.4)
cl B
Number of patients with at least one event 39 (19.3%) 36 (20.3%) 31 (19.1%) -1.0 (-9.1 - 7.0)
cl A
Number of patients with at least one event 31 (15.3%) 24 (13.6%) 27 (16.7%) 1.8 (-5.3 - 8.9)
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
cl D
Number of patients with at least one event 40 (19.8%) 40 (22.6%) 29 (17.9%) -2.8 (-11.1 - 5.5)
Number of events 66 57 43 -2.8 (-11.1 - 5.5)
cl D (n) 40 40 29 -2.8 (-11.1 - 5.5)
cl C
Number of patients with at least one event 31 (15.3%) 23 (13.0%) 25 (15.4%) 2.4 (-4.7 - 9.4)
Number of events 38 30 33 2.4 (-4.7 - 9.4)
cl C (n) 31 23 25 2.4 (-4.7 - 9.4)
cl B
Number of patients with at least one event 39 (19.3%) 36 (20.3%) 31 (19.1%) -1.0 (-9.1 - 7.0)
Number of events 59 57 51 -1.0 (-9.1 - 7.0)
cl B (n) 39 36 31 -1.0 (-9.1 - 7.0)
cl A
Number of patients with at least one event 31 (15.3%) 24 (13.6%) 27 (16.7%) 1.8 (-5.3 - 8.9)
Number of events 39 33 35 1.8 (-5.3 - 8.9)
cl A (n) 31 24 27 1.8 (-5.3 - 8.9)
analyze_num_patients works as expected with risk difference column
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
—————————————————————————————————————————————————————————————————————————————————
Any SAE 59 (29.2%) 57 (32.2%) 48 (29.6%) -3.0 (-12.3 - 6.3)
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
—————————————————————————————————————————————————————————————————————————————————
Any SAE 59 (29.2%) 57 (32.2%) 48 (29.6%) -3.0 (-12.3 - 6.3)
202 177 162 -3.0 (-12.3 - 6.3)
(n) 59 57 48 -3.0 (-12.3 - 6.3)
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s_num_patients works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients works as expected with empty input
Code
res
Output
$unique
[1] 0 0
attr(,"label")
[1] ""
$nonunique
[1] 0
attr(,"label")
[1] ""
$unique_count
[1] 0
attr(,"label")
[1] "(n)"
s_num_patients works as expected with unique_count_suffix = FALSE
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] ""
s_num_patients_content works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
summarize_num_patients works as expected with healthy input
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Number of events 4 4
(n) 3 3
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Code
res
Output
A B
(N=5) (N=4)
————————————————————————————————
Number of events 4 4
Code
res
Output
A B
(N=5) (N=4)
———————————————————
(n) 3 3
s_num_patients count_by works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients count_by with missing works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients count_by with missing case 2 works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 3
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients_content with count_by works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 3
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients_content with count_by case 2 works as expected with healthy input
Code
res
Output
$unique
[1] 3.0 0.6
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 3
attr(,"label")
[1] "(n)"
s_num_patients_content with count_by trivial cases, identical to without count_by
Code
res
Output
$unique
[1] 4.0 0.8
attr(,"label")
[1] ""
$nonunique
[1] 4
attr(,"label")
[1] ""
$unique_count
[1] 4
attr(,"label")
[1] "(n)"
summarize_num_patients with count_by works as expected with healthy input
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Number of events 3 3
(n) 3 3
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Code
res
Output
A B
(N=5) (N=4)
————————————————————————————————
Number of events 3 3
Code
res
Output
A B
(N=5) (N=4)
———————————————————
(n) 3 3
summarize_num_patients with count_by different combinations works as expected with healthy input
Code
res
Output
A B
(N=5) (N=4)
——————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%)
Number of events 4 3
(n) 3 3
analyze_num_patients works well for pagination
Code
res
Output
A B A+B
(N=5) (N=4) (N=9)
————————————————————————————————————————————————————————————————————————————————
Number of patients with at least one event 3 (60.0%) 3 (75.0%) 6 (66.7%)
Number of events 4 4 8
e 1.1
Number of patients with at least one event 2 (40.0%) 2 (50.0%) 4 (44.4%)
Number of events 3 3 6
11 1 (20.0%) 1 (25.0%) 2 (22.2%)
19 0 1 (25.0%) 1 (11.1%)
10 1 (20.0%) 0 1 (11.1%)
17 1 (20.0%) 0 1 (11.1%)
f 1.1
Number of patients with at least one event 1 (20.0%) 1 (25.0%) 2 (22.2%)
Number of events 1 1 2
17 0 1 (25.0%) 1 (11.1%)
15 1 (20.0%) 0 1 (11.1%)
summarize_num_patients works as expected with risk difference column
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
cl D
Number of patients with at least one event 40 (19.8%) 40 (22.6%) 29 (17.9%) -2.8 (-11.1 - 5.5)
cl C
Number of patients with at least one event 31 (15.3%) 23 (13.0%) 25 (15.4%) 2.4 (-4.7 - 9.4)
cl B
Number of patients with at least one event 39 (19.3%) 36 (20.3%) 31 (19.1%) -1.0 (-9.1 - 7.0)
cl A
Number of patients with at least one event 31 (15.3%) 24 (13.6%) 27 (16.7%) 1.8 (-5.3 - 8.9)
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
cl D
Number of patients with at least one event 40 (19.8%) 40 (22.6%) 29 (17.9%) -2.8 (-11.1 - 5.5)
Number of events 66 57 43 -2.8 (-11.1 - 5.5)
cl D (n) 40 40 29 -2.8 (-11.1 - 5.5)
cl C
Number of patients with at least one event 31 (15.3%) 23 (13.0%) 25 (15.4%) 2.4 (-4.7 - 9.4)
Number of events 38 30 33 2.4 (-4.7 - 9.4)
cl C (n) 31 23 25 2.4 (-4.7 - 9.4)
cl B
Number of patients with at least one event 39 (19.3%) 36 (20.3%) 31 (19.1%) -1.0 (-9.1 - 7.0)
Number of events 59 57 51 -1.0 (-9.1 - 7.0)
cl B (n) 39 36 31 -1.0 (-9.1 - 7.0)
cl A
Number of patients with at least one event 31 (15.3%) 24 (13.6%) 27 (16.7%) 1.8 (-5.3 - 8.9)
Number of events 39 33 35 1.8 (-5.3 - 8.9)
cl A (n) 31 24 27 1.8 (-5.3 - 8.9)
analyze_num_patients works as expected with risk difference column
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
—————————————————————————————————————————————————————————————————————————————————
Any SAE 59 (29.2%) 57 (32.2%) 48 (29.6%) -3.0 (-12.3 - 6.3)
Code
res
Output
A: Drug X B: Placebo C: Combination Risk Difference (%) (95% CI)
(N=202) (N=177) (N=162) (N=379)
—————————————————————————————————————————————————————————————————————————————————
Any SAE 59 (29.2%) 57 (32.2%) 48 (29.6%) -3.0 (-12.3 - 6.3)
202 177 162 -3.0 (-12.3 - 6.3)
(n) 59 57 48 -3.0 (-12.3 - 6.3)
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