Nothing
Code
tbl1
Output
# A tibble: 8 x 8
variable var_type var_label row_type label stat_1 stat_2 stat_0
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 grade categorical Grade label Grade <NA> <NA> <NA>
2 grade categorical Grade level I 45.9 46.4 46.2
3 grade categorical Grade level II 44.6 50.3 47.5
4 grade categorical Grade level III 51.0 45.7 48.1
5 response dichotomous Tumor Response label Tumor~ 50.1 49.5 49.8
6 response dichotomous Tumor Response missing Unkno~ 3 4 7
7 marker continuous Marker Level (ng/mL) label Marke~ 46.5 47.5 47.0
8 marker continuous Marker Level (ng/mL) missing Unkno~ 6 4 10
Code
tbl
Output
# A tibble: 10 x 5
label n stat_0 stat_1 stat_2
<chr> <chr> <chr> <chr> <chr>
1 __Grade__ 200 <NA> <NA> <NA>
2 _I_ <NA> 1.1 (high, diff: 0.2) 1.2 (high, diff: ~ 1.0 (~
3 _II_ <NA> 0.7 (low, diff: -0.2) 0.9 (low, diff: -~ 0.5 (~
4 _III_ <NA> 1.0 (high, diff: 0.1) 1.0 (high, diff: ~ 1.0 (~
5 __T Stage__ 200 <NA> <NA> <NA>
6 _T1_ <NA> 0.7 (low, diff: -0.2) 0.7 (low, diff: -~ 0.7 (~
7 _T2_ <NA> 1.1 (high, diff: 0.2) 1.2 (high, diff: ~ 1.0 (~
8 _T3_ <NA> 1.0 (high, diff: 0.1) 1.1 (high, diff: ~ 0.9 (~
9 _T4_ <NA> 0.9 (low, diff: -0.1) 1.1 (high, diff: ~ 0.7 (~
10 __All grades & stages__ 200 0.9 (low, diff: 0.0) 1.0 (high, diff: ~ 0.8 (~
Code
tbl
Output
# A tibble: 3 x 3
label stat_1 stat_2
<chr> <chr> <chr>
1 Marker Level (ng/mL) 1.02 [0.83; 1.20] 0.82 [0.65; 0.99]
2 Unknown 6 4
3 Months to Death/Censor 20.2 [19.2; 21.2] 19.0 [18.0; 20.1]
Code
tbl
Output
# A tibble: 6 x 3
label stat_1 stat_2
<chr> <chr> <chr>
1 Overall 46 48
2 Grade <NA> <NA>
3 I 46 48
4 II 45 51
5 III 52 45
6 IV NA NA
Code
tbl
Output
# A tibble: 5 x 3
label stat_1 stat_2
<chr> <chr> <chr>
1 T Stage <NA> <NA>
2 T1 0.012 [0.00; 0.02] (7/583) 0.021 [0.01; 0.04] (11/522)
3 T2 0.011 [0.00; 0.02] (6/528) 0.012 [0.01; 0.03] (7/560)
4 T3 0.019 [0.01; 0.04] (8/426) 0.016 [0.01; 0.03] (7/425)
5 T4 0.016 [0.01; 0.03] (7/445) 0.018 [0.01; 0.04] (8/434)
Code
tbl
Output
# A tibble: 4 x 3
label stat_1 stat_2
<chr> <chr> <chr>
1 Grade <NA> <NA>
2 I 46 [36-60] 48 [42-55]
3 II 45 [31-55] 51 [43-57]
4 III 52 [42-60] 45 [36-52]
Code
tbl
Output
# A tibble: 8 x 3
label stat_1 stat_2
<chr> <chr> <chr>
1 Age <NA> <NA>
2 Child 45.3% (29/64) [33-58] 62.2% (28/45) [47-76]
3 Adult 20.3% (338/1,667) [18-22] 74.4% (316/425) [70-78]
4 Class <NA> <NA>
5 1st 34.4% (62/180) [28-42] 97.2% (141/145) [93-99]
6 2nd 14.0% (25/179) [9.4-20] 87.7% (93/106) [80-93]
7 3rd 17.3% (88/510) [14-21] 45.9% (90/196) [39-53]
8 Crew 22.3% (192/862) [20-25] 87.0% (20/23) [65-97]
Code
res
Output
# A tibble: 2 x 2
`**Characteristic**` `**N = 200**`
<chr> <chr>
1 Age 189/200
2 Unknown 11
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