Nothing
Code
tbl_diff %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 98 **Drug B**, N = 102 **Difference**
1 Marker Level (ng/mL) 0.84 (0.24, 1.57) 0.52 (0.19, 1.20) 0.20
2 Age 46 (37, 59) 48 (39, 56) -0.44
**95% CI** **p-value**
1 -0.05, 0.44 0.12
2 -4.6, 3.7 0.8
Code
trial %>% select(trt, response, grade) %>% tbl_summary(by = trt, percent = "row") %>%
add_difference() %>% as.data.frame()
Message
i `add_difference()` results for categorical variables may not compatible
with `tbl_summary(percent = c("cell", "row"))` options. Use column
percentages, `tbl_summary(percent = "column")`.
Output
**Characteristic** **Drug A**, N = 98 **Drug B**, N = 102 **Difference**
1 Tumor Response 28 (46%) 33 (54%) -8.2%
2 Unknown 3 4 <NA>
3 Grade <NA> <NA> 0.07
4 I 35 (51%) 33 (49%) <NA>
5 II 32 (47%) 36 (53%) <NA>
6 III 31 (48%) 33 (52%) <NA>
**95% CI** **p-value**
1 -28%, 11% 0.5
2 <NA> <NA>
3 -0.20, 0.35 <NA>
4 <NA> <NA>
5 <NA> <NA>
6 <NA> <NA>
Code
tbl_test.args %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 98 **Drug B**, N = 102 **Difference**
1 Age 46 (37, 59) 48 (39, 56) -0.44
2 Age 46 (37, 59) 48 (39, 56) -0.44
3 Age 46 (37, 59) 48 (39, 56) <NA>
4 Age 46 (37, 59) 48 (39, 56) <NA>
5 Tumor Response 28 (29%) 33 (34%) -4.2%
6 Tumor Response 28 (29%) 33 (34%) -4.2%
7 Age 46 (37, 59) 48 (39, 56) -0.44
8 Age 46 (37, 59) 48 (39, 56) -0.03
**95% CI** **p-value**
1 -4.6, 3.7 0.8
2 -4.6, 3.7 0.8
3 <NA> 0.7
4 <NA> 0.7
5 -18%, 9.9% 0.6
6 -16%, 100% 0.7
7 -4.6, 3.7 0.8
8 -0.32, 0.25 <NA>
Code
tbl_groups %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 98 **Drug B**, N = 102
1 Age 46 (37, 59) 48 (39, 56)
**Adjusted Difference** **95% CI**
1 -1.1 -4.7, 2.4
Code
tbl1
Output
# A tibble: 4 x 6
label stat_1 stat_2 estimate ci p.value
<chr> <chr> <chr> <chr> <chr> <chr>
1 Age 47 (15) 47 (14) -0.44 -4.6, 3.7 0.8
2 Marker Level (ng/mL) 1.02 (0.89) 0.82 (0.83) 0.20 -0.05, 0.44 0.12
3 Tumor Response 29% 34% -4.2% -18%, 9.9% 0.6
4 Patient Died 53% 59% -5.8% -21%, 9.0% 0.5
Code
t1 %>% as.data.frame()
Output
**Characteristic** **0**, N = 19 **1**, N = 13 **p-value**
1 mpg 0 (NA%) 0 (NA%) <NA>
2 hp NA (NA, NA) NA (NA, NA) <NA>
Code
tbl
Output
# A tibble: 6 x 5
label stat_1 stat_2 estimate ci
<chr> <chr> <chr> <chr> <chr>
1 Age 46 (37, 59) 48 (39, 56) -0.03 -0.32, 0.25
2 Tumor Response 28 (29%) 33 (34%) -0.09 -0.37, 0.19
3 Grade <NA> <NA> 0.07 -0.20, 0.35
4 I 35 (36%) 33 (32%) <NA> <NA>
5 II 32 (33%) 36 (35%) <NA> <NA>
6 III 31 (32%) 33 (32%) <NA> <NA>
Code
tbl
Output
# A tibble: 8 x 5
label stat_1 stat_2 estimate ci
<chr> <chr> <chr> <chr> <chr>
1 age 61 (17) 61 (16) 0.003 -0.068, 0.075
2 sex <NA> <NA> 0.003 -0.068, 0.074
3 Female 647 (42%) 648 (43%) <NA> <NA>
4 Male 876 (58%) 872 (57%) <NA> <NA>
5 race <NA> <NA> 0.009 -0.062, 0.080
6 black 238 (16%) 236 (16%) <NA> <NA>
7 other 95 (6.2%) 98 (6.4%) <NA> <NA>
8 white 1,190 (78%) 1,187 (78%) <NA> <NA>
Code
res %>% as.data.frame()
Output
**Characteristic** **Drug A**, N = 98 **Drug B**, N = 102
1 Age 46 (37, 59) 48 (39, 56)
2 Tumor Response 28 (29%) 33 (34%)
**Adjusted Difference** **95% CI** **p-value**
1 -0.42 -4.5, 3.7 0.8
2 -4.7% -18%, 8.4% 0.5
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.