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tests/testthat/_snaps/tbl_strata.md
In gtsummary: Presentation-Ready Data Summary and Analytic Result Tables
no errors with standard use
Code
tbl %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 35 **Drug B**, N = 33 **p-value**
1 Age 46 (36, 60) 48 (42, 55) 0.6
2 Unknown 2 0 <NA>
3 T Stage <NA> <NA> 0.8
4 T1 8 (23%) 9 (27%) <NA>
5 T2 8 (23%) 10 (30%) <NA>
6 T3 11 (31%) 7 (21%) <NA>
7 T4 8 (23%) 7 (21%) <NA>
**Drug A**, N = 32 **Drug B**, N = 36 **p-value** **Drug A**, N = 31
1 45 (31, 55) 51 (43, 57) 0.10 52 (42, 60)
2 2 4 <NA> 3
3 <NA> <NA> 0.3 <NA>
4 14 (44%) 9 (25%) <NA> 6 (19%)
5 8 (25%) 9 (25%) <NA> 9 (29%)
6 5 (16%) 6 (17%) <NA> 6 (19%)
7 5 (16%) 12 (33%) <NA> 10 (32%)
**Drug B**, N = 33 **p-value**
1 45 (36, 52) 0.10
2 0 <NA>
3 <NA> >0.9
4 7 (21%) <NA>
5 10 (30%) <NA>
6 8 (24%) <NA>
7 8 (24%) <NA>
Code
trial %>% select(age, grade, stage, trt) %>% mutate(grade = paste("Grade",
grade), stage = paste("Stage", stage)) %>% tbl_strata(strata = c(grade, stage),
.tbl_fun = ~ .x %>% tbl_summary(by = trt) %>% add_p(test = all_continuous() ~
"t.test")) %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 8 **Drug B**, N = 9 **p-value**
1 Age 40 (34, 49) 48 (43, 66) 0.5
2 Unknown 2 0 <NA>
**Drug A**, N = 8 **Drug B**, N = 10 **p-value** **Drug A**, N = 11
1 47 (41, 49) 48 (44, 54) >0.9 48 (37, 61)
2 <NA> <NA> <NA> <NA>
**Drug B**, N = 7 **p-value** **Drug A**, N = 8 **Drug B**, N = 7 **p-value**
1 53 (42, 60) 0.9 40 (30, 60) 43 (39, 48) >0.9
2 <NA> <NA> <NA> <NA> <NA>
**Drug A**, N = 14 **Drug B**, N = 9 **p-value** **Drug A**, N = 8
1 43 (31, 47) 48 (44, 57) 0.071 51 (36, 59)
2 <NA> <NA> <NA> <NA>
**Drug B**, N = 9 **p-value** **Drug A**, N = 5 **Drug B**, N = 6 **p-value**
1 49 (38, 49) 0.5 47 (38, 54) 57 (54, 59) 0.3
2 <NA> <NA> 1 0 <NA>
**Drug A**, N = 5 **Drug B**, N = 12 **p-value** **Drug A**, N = 6
1 46 (29, 62) 53 (38, 60) 0.6 55 (42, 63)
2 1 4 <NA> <NA>
**Drug B**, N = 7 **p-value** **Drug A**, N = 9 **Drug B**, N = 10
1 43 (39, 48) 0.8 53 (43, 66) 50 (37, 53)
2 <NA> <NA> 1 0
**p-value** **Drug A**, N = 6 **Drug B**, N = 8 **p-value**
1 0.3 48 (39, 58) 44 (38, 54) 0.7
2 <NA> 1 0 <NA>
**Drug A**, N = 10 **Drug B**, N = 8 **p-value**
1 51 (45, 54) 42 (34, 51) 0.3
2 1 0 <NA>
Code
tbl %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 35 **Drug B**, N = 33 **Drug A**, N = 32
1 Age 46 (36, 60) 48 (42, 55) 45 (31, 55)
2 T Stage <NA> <NA> <NA>
3 T1 8 (23%) 9 (27%) 14 (44%)
4 T2 8 (23%) 10 (30%) 8 (25%)
5 T3 11 (31%) 7 (21%) 5 (16%)
6 T4 8 (23%) 7 (21%) 5 (16%)
**Drug B**, N = 36 **Drug A**, N = 31 **Drug B**, N = 33
1 51 (43, 57) 52 (42, 60) 45 (36, 52)
2 <NA> <NA> <NA>
3 9 (25%) 6 (19%) 7 (21%)
4 9 (25%) 9 (29%) 10 (30%)
5 6 (17%) 6 (19%) 8 (24%)
6 12 (33%) 10 (32%) 8 (24%)
Code
tbl %>% as.data.frame()
Output
**Group** **Characteristic** **Drug A**, N = 35 **Drug B**, N = 33
1 Grade I Age 46 (36, 60) 48 (42, 55)
2 <NA> Unknown 2 0
3 <NA> T Stage <NA> <NA>
4 <NA> T1 8 (23%) 9 (27%)
5 <NA> T2 8 (23%) 10 (30%)
6 <NA> T3 11 (31%) 7 (21%)
7 <NA> T4 8 (23%) 7 (21%)
8 Grade II Age 45 (31, 55) 51 (43, 57)
9 <NA> Unknown 2 4
10 <NA> T Stage <NA> <NA>
11 <NA> T1 14 (44%) 9 (25%)
12 <NA> T2 8 (25%) 9 (25%)
13 <NA> T3 5 (16%) 6 (17%)
14 <NA> T4 5 (16%) 12 (33%)
15 Grade III Age 52 (42, 60) 45 (36, 52)
16 <NA> Unknown 3 0
17 <NA> T Stage <NA> <NA>
18 <NA> T1 6 (19%) 7 (21%)
19 <NA> T2 9 (29%) 10 (30%)
20 <NA> T3 6 (19%) 8 (24%)
21 <NA> T4 10 (32%) 8 (24%)
**p-value**
1 0.6
2 <NA>
3 0.8
4 <NA>
5 <NA>
6 <NA>
7 <NA>
8 0.10
9 <NA>
10 0.3
11 <NA>
12 <NA>
13 <NA>
14 <NA>
15 0.10
16 <NA>
17 >0.9
18 <NA>
19 <NA>
20 <NA>
21 <NA>
Code
trial %>% select(age, grade, stage, trt) %>% mutate(grade = paste("Grade",
grade)) %>% tbl_strata(strata = grade, .tbl_fun = ~ .x %>% tbl_uvregression(
y = age, method = lm)) %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value** **N** **Beta**
1 T Stage 66 <NA> <NA> <NA> 62 <NA>
2 T1 <NA> <NA> <NA> <NA> <NA> <NA>
3 T2 <NA> -1.1 -12, 9.5 0.8 <NA> 2.9
4 T3 <NA> 2.3 -8.4, 13 0.7 <NA> 7.3
5 T4 <NA> -5.7 -17, 5.4 0.3 <NA> 2.9
6 Chemotherapy Treatment 66 <NA> <NA> <NA> 62 <NA>
7 Drug A <NA> <NA> <NA> <NA> <NA> <NA>
8 Drug B <NA> 0.55 -7.0, 8.1 0.9 <NA> 5.7
**95% CI** **p-value** **N** **Beta** **95% CI** **p-value**
1 <NA> <NA> 61 <NA> <NA> <NA>
2 <NA> <NA> <NA> <NA> <NA> <NA>
3 -6.0, 12 0.5 <NA> 0.93 -9.5, 11 0.9
4 -3.2, 18 0.2 <NA> -2.4 -14, 8.9 0.7
5 -6.9, 13 0.6 <NA> -4.0 -15, 6.6 0.5
6 <NA> <NA> 61 <NA> <NA> <NA>
7 <NA> <NA> <NA> <NA> <NA> <NA>
8 -1.1, 13 0.10 <NA> -5.3 -12, 1.9 0.15
Code
trial %>% select(grade, stage, trt) %>% mutate(grade = paste("Grade", grade)) %>%
tbl_strata(strata = grade, .tbl_fun = ~ .x %>% tbl_cross() %>% add_p()) %>%
as.data.frame()
Output
Drug A Drug B Total p-value Drug A Drug B Total p-value Drug A Drug B
1 T Stage <NA> <NA> <NA> 0.8 <NA> <NA> <NA> 0.3 <NA> <NA>
2 T1 8 9 17 <NA> 14 9 23 <NA> 6 7
3 T2 8 10 18 <NA> 8 9 17 <NA> 9 10
4 T3 11 7 18 <NA> 5 6 11 <NA> 6 8
5 T4 8 7 15 <NA> 5 12 17 <NA> 10 8
6 Total 35 33 68 <NA> 32 36 68 <NA> 31 33
Total p-value
1 <NA> >0.9
2 13 <NA>
3 19 <NA>
4 14 <NA>
5 18 <NA>
6 64 <NA>
Code
trial %>% select(grade, stage, trt) %>% mutate(grade = paste("Grade", grade)) %>%
tbl_strata(strata = grade, .tbl_fun = ~ .x %>% tbl_cross() %>% add_p()) %>%
as.data.frame()
Output
Drug A Drug B Total p-value Drug A Drug B Total p-value Drug A Drug B
1 T Stage <NA> <NA> <NA> 0.8 <NA> <NA> <NA> 0.3 <NA> <NA>
2 T1 8 9 17 <NA> 14 9 23 <NA> 6 7
3 T2 8 10 18 <NA> 8 9 17 <NA> 9 10
4 T3 11 7 18 <NA> 5 6 11 <NA> 6 8
5 T4 8 7 15 <NA> 5 12 17 <NA> 10 8
6 Total 35 33 68 <NA> 32 36 68 <NA> 31 33
Total p-value
1 <NA> >0.9
2 13 <NA>
3 19 <NA>
4 14 <NA>
5 18 <NA>
6 64 <NA>
Code
trial %>% select(grade, response) %>% tbl_strata2(strata = grade, .tbl_fun = ~
.x %>% tbl_summary(include = response, label = list(response = .y), missing = "no")) %>%
as.data.frame()
Output
**Characteristic** **N = 68** **N = 68** **N = 64**
1 **I** 21 (31%) <NA> <NA>
2 **II** <NA> 19 (30%) <NA>
3 **III** <NA> <NA> 21 (33%)
Code
survey::svydesign(~1, data = trial, weights = ~1) %>% tbl_strata(strata = grade,
~ tbl_svysummary(.x, by = trt, include = c(stage, trt), percent = "cell") %>%
modify_header(all_stat_cols() ~ "**{level}**"), .combine_with = "tbl_stack") %>%
as.data.frame()
Output
**Group** **Characteristic** **Drug A** **Drug B**
1 I stage <NA> <NA>
2 <NA> T1 8 (12%) 9 (13%)
3 <NA> T2 8 (12%) 10 (15%)
4 <NA> T3 11 (16%) 7 (10%)
5 <NA> T4 8 (12%) 7 (10%)
6 II stage <NA> <NA>
7 <NA> T1 14 (21%) 9 (13%)
8 <NA> T2 8 (12%) 9 (13%)
9 <NA> T3 5 (7.4%) 6 (8.8%)
10 <NA> T4 5 (7.4%) 12 (18%)
11 III stage <NA> <NA>
12 <NA> T1 6 (9.4%) 7 (11%)
13 <NA> T2 9 (14%) 10 (16%)
14 <NA> T3 6 (9.4%) 8 (13%)
15 <NA> T4 10 (16%) 8 (13%)
Code
tbl %>% as.data.frame()
Output
**Characteristic** **N = 98** **N = 102**
1 Grade <NA> <NA>
2 I 35 (36%) 33 (32%)
3 II 32 (33%) 36 (35%)
4 III 31 (32%) 33 (32%)
5 T Stage <NA> <NA>
6 T1 28 (29%) 25 (25%)
7 T2 25 (26%) 29 (28%)
8 T3 22 (22%) 21 (21%)
9 T4 23 (23%) 27 (26%)
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no errors with standard use
Code
tbl %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 35 **Drug B**, N = 33 **p-value**
1 Age 46 (36, 60) 48 (42, 55) 0.6
2 Unknown 2 0 <NA>
3 T Stage <NA> <NA> 0.8
4 T1 8 (23%) 9 (27%) <NA>
5 T2 8 (23%) 10 (30%) <NA>
6 T3 11 (31%) 7 (21%) <NA>
7 T4 8 (23%) 7 (21%) <NA>
**Drug A**, N = 32 **Drug B**, N = 36 **p-value** **Drug A**, N = 31
1 45 (31, 55) 51 (43, 57) 0.10 52 (42, 60)
2 2 4 <NA> 3
3 <NA> <NA> 0.3 <NA>
4 14 (44%) 9 (25%) <NA> 6 (19%)
5 8 (25%) 9 (25%) <NA> 9 (29%)
6 5 (16%) 6 (17%) <NA> 6 (19%)
7 5 (16%) 12 (33%) <NA> 10 (32%)
**Drug B**, N = 33 **p-value**
1 45 (36, 52) 0.10
2 0 <NA>
3 <NA> >0.9
4 7 (21%) <NA>
5 10 (30%) <NA>
6 8 (24%) <NA>
7 8 (24%) <NA>
Code
trial %>% select(age, grade, stage, trt) %>% mutate(grade = paste("Grade",
grade), stage = paste("Stage", stage)) %>% tbl_strata(strata = c(grade, stage),
.tbl_fun = ~ .x %>% tbl_summary(by = trt) %>% add_p(test = all_continuous() ~
"t.test")) %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 8 **Drug B**, N = 9 **p-value**
1 Age 40 (34, 49) 48 (43, 66) 0.5
2 Unknown 2 0 <NA>
**Drug A**, N = 8 **Drug B**, N = 10 **p-value** **Drug A**, N = 11
1 47 (41, 49) 48 (44, 54) >0.9 48 (37, 61)
2 <NA> <NA> <NA> <NA>
**Drug B**, N = 7 **p-value** **Drug A**, N = 8 **Drug B**, N = 7 **p-value**
1 53 (42, 60) 0.9 40 (30, 60) 43 (39, 48) >0.9
2 <NA> <NA> <NA> <NA> <NA>
**Drug A**, N = 14 **Drug B**, N = 9 **p-value** **Drug A**, N = 8
1 43 (31, 47) 48 (44, 57) 0.071 51 (36, 59)
2 <NA> <NA> <NA> <NA>
**Drug B**, N = 9 **p-value** **Drug A**, N = 5 **Drug B**, N = 6 **p-value**
1 49 (38, 49) 0.5 47 (38, 54) 57 (54, 59) 0.3
2 <NA> <NA> 1 0 <NA>
**Drug A**, N = 5 **Drug B**, N = 12 **p-value** **Drug A**, N = 6
1 46 (29, 62) 53 (38, 60) 0.6 55 (42, 63)
2 1 4 <NA> <NA>
**Drug B**, N = 7 **p-value** **Drug A**, N = 9 **Drug B**, N = 10
1 43 (39, 48) 0.8 53 (43, 66) 50 (37, 53)
2 <NA> <NA> 1 0
**p-value** **Drug A**, N = 6 **Drug B**, N = 8 **p-value**
1 0.3 48 (39, 58) 44 (38, 54) 0.7
2 <NA> 1 0 <NA>
**Drug A**, N = 10 **Drug B**, N = 8 **p-value**
1 51 (45, 54) 42 (34, 51) 0.3
2 1 0 <NA>
Code
tbl %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 35 **Drug B**, N = 33 **Drug A**, N = 32
1 Age 46 (36, 60) 48 (42, 55) 45 (31, 55)
2 T Stage <NA> <NA> <NA>
3 T1 8 (23%) 9 (27%) 14 (44%)
4 T2 8 (23%) 10 (30%) 8 (25%)
5 T3 11 (31%) 7 (21%) 5 (16%)
6 T4 8 (23%) 7 (21%) 5 (16%)
**Drug B**, N = 36 **Drug A**, N = 31 **Drug B**, N = 33
1 51 (43, 57) 52 (42, 60) 45 (36, 52)
2 <NA> <NA> <NA>
3 9 (25%) 6 (19%) 7 (21%)
4 9 (25%) 9 (29%) 10 (30%)
5 6 (17%) 6 (19%) 8 (24%)
6 12 (33%) 10 (32%) 8 (24%)
Code
tbl %>% as.data.frame()
Output
**Group** **Characteristic** **Drug A**, N = 35 **Drug B**, N = 33
1 Grade I Age 46 (36, 60) 48 (42, 55)
2 <NA> Unknown 2 0
3 <NA> T Stage <NA> <NA>
4 <NA> T1 8 (23%) 9 (27%)
5 <NA> T2 8 (23%) 10 (30%)
6 <NA> T3 11 (31%) 7 (21%)
7 <NA> T4 8 (23%) 7 (21%)
8 Grade II Age 45 (31, 55) 51 (43, 57)
9 <NA> Unknown 2 4
10 <NA> T Stage <NA> <NA>
11 <NA> T1 14 (44%) 9 (25%)
12 <NA> T2 8 (25%) 9 (25%)
13 <NA> T3 5 (16%) 6 (17%)
14 <NA> T4 5 (16%) 12 (33%)
15 Grade III Age 52 (42, 60) 45 (36, 52)
16 <NA> Unknown 3 0
17 <NA> T Stage <NA> <NA>
18 <NA> T1 6 (19%) 7 (21%)
19 <NA> T2 9 (29%) 10 (30%)
20 <NA> T3 6 (19%) 8 (24%)
21 <NA> T4 10 (32%) 8 (24%)
**p-value**
1 0.6
2 <NA>
3 0.8
4 <NA>
5 <NA>
6 <NA>
7 <NA>
8 0.10
9 <NA>
10 0.3
11 <NA>
12 <NA>
13 <NA>
14 <NA>
15 0.10
16 <NA>
17 >0.9
18 <NA>
19 <NA>
20 <NA>
21 <NA>
Code
trial %>% select(age, grade, stage, trt) %>% mutate(grade = paste("Grade",
grade)) %>% tbl_strata(strata = grade, .tbl_fun = ~ .x %>% tbl_uvregression(
y = age, method = lm)) %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value** **N** **Beta**
1 T Stage 66 <NA> <NA> <NA> 62 <NA>
2 T1 <NA> <NA> <NA> <NA> <NA> <NA>
3 T2 <NA> -1.1 -12, 9.5 0.8 <NA> 2.9
4 T3 <NA> 2.3 -8.4, 13 0.7 <NA> 7.3
5 T4 <NA> -5.7 -17, 5.4 0.3 <NA> 2.9
6 Chemotherapy Treatment 66 <NA> <NA> <NA> 62 <NA>
7 Drug A <NA> <NA> <NA> <NA> <NA> <NA>
8 Drug B <NA> 0.55 -7.0, 8.1 0.9 <NA> 5.7
**95% CI** **p-value** **N** **Beta** **95% CI** **p-value**
1 <NA> <NA> 61 <NA> <NA> <NA>
2 <NA> <NA> <NA> <NA> <NA> <NA>
3 -6.0, 12 0.5 <NA> 0.93 -9.5, 11 0.9
4 -3.2, 18 0.2 <NA> -2.4 -14, 8.9 0.7
5 -6.9, 13 0.6 <NA> -4.0 -15, 6.6 0.5
6 <NA> <NA> 61 <NA> <NA> <NA>
7 <NA> <NA> <NA> <NA> <NA> <NA>
8 -1.1, 13 0.10 <NA> -5.3 -12, 1.9 0.15
Code
trial %>% select(grade, stage, trt) %>% mutate(grade = paste("Grade", grade)) %>%
tbl_strata(strata = grade, .tbl_fun = ~ .x %>% tbl_cross() %>% add_p()) %>%
as.data.frame()
Output
Drug A Drug B Total p-value Drug A Drug B Total p-value Drug A Drug B
1 T Stage <NA> <NA> <NA> 0.8 <NA> <NA> <NA> 0.3 <NA> <NA>
2 T1 8 9 17 <NA> 14 9 23 <NA> 6 7
3 T2 8 10 18 <NA> 8 9 17 <NA> 9 10
4 T3 11 7 18 <NA> 5 6 11 <NA> 6 8
5 T4 8 7 15 <NA> 5 12 17 <NA> 10 8
6 Total 35 33 68 <NA> 32 36 68 <NA> 31 33
Total p-value
1 <NA> >0.9
2 13 <NA>
3 19 <NA>
4 14 <NA>
5 18 <NA>
6 64 <NA>
Code
trial %>% select(grade, stage, trt) %>% mutate(grade = paste("Grade", grade)) %>%
tbl_strata(strata = grade, .tbl_fun = ~ .x %>% tbl_cross() %>% add_p()) %>%
as.data.frame()
Output
Drug A Drug B Total p-value Drug A Drug B Total p-value Drug A Drug B
1 T Stage <NA> <NA> <NA> 0.8 <NA> <NA> <NA> 0.3 <NA> <NA>
2 T1 8 9 17 <NA> 14 9 23 <NA> 6 7
3 T2 8 10 18 <NA> 8 9 17 <NA> 9 10
4 T3 11 7 18 <NA> 5 6 11 <NA> 6 8
5 T4 8 7 15 <NA> 5 12 17 <NA> 10 8
6 Total 35 33 68 <NA> 32 36 68 <NA> 31 33
Total p-value
1 <NA> >0.9
2 13 <NA>
3 19 <NA>
4 14 <NA>
5 18 <NA>
6 64 <NA>
Code
trial %>% select(grade, response) %>% tbl_strata2(strata = grade, .tbl_fun = ~
.x %>% tbl_summary(include = response, label = list(response = .y), missing = "no")) %>%
as.data.frame()
Output
**Characteristic** **N = 68** **N = 68** **N = 64**
1 **I** 21 (31%) <NA> <NA>
2 **II** <NA> 19 (30%) <NA>
3 **III** <NA> <NA> 21 (33%)
Code
survey::svydesign(~1, data = trial, weights = ~1) %>% tbl_strata(strata = grade,
~ tbl_svysummary(.x, by = trt, include = c(stage, trt), percent = "cell") %>%
modify_header(all_stat_cols() ~ "**{level}**"), .combine_with = "tbl_stack") %>%
as.data.frame()
Output
**Group** **Characteristic** **Drug A** **Drug B**
1 I stage <NA> <NA>
2 <NA> T1 8 (12%) 9 (13%)
3 <NA> T2 8 (12%) 10 (15%)
4 <NA> T3 11 (16%) 7 (10%)
5 <NA> T4 8 (12%) 7 (10%)
6 II stage <NA> <NA>
7 <NA> T1 14 (21%) 9 (13%)
8 <NA> T2 8 (12%) 9 (13%)
9 <NA> T3 5 (7.4%) 6 (8.8%)
10 <NA> T4 5 (7.4%) 12 (18%)
11 III stage <NA> <NA>
12 <NA> T1 6 (9.4%) 7 (11%)
13 <NA> T2 9 (14%) 10 (16%)
14 <NA> T3 6 (9.4%) 8 (13%)
15 <NA> T4 10 (16%) 8 (13%)
Code
tbl %>% as.data.frame()
Output
**Characteristic** **N = 98** **N = 102**
1 Grade <NA> <NA>
2 I 35 (36%) 33 (32%)
3 II 32 (33%) 36 (35%)
4 III 31 (32%) 33 (32%)
5 T Stage <NA> <NA>
6 T1 28 (29%) 25 (25%)
7 T2 25 (26%) 29 (28%)
8 T3 22 (22%) 21 (21%)
9 T4 23 (23%) 27 (26%)
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