Written to support stratified tables to summary_factorlist. See
example below for explantion.
colname2label(.data, .cols)
| .data | Data frame |
|---|---|
| .cols | Quoted character vector of columns to change |
library(rlang) library(dplyr) explanatory = c("age.factor", "sex.factor") dependent = "perfor.factor" # Pick option below split = "rx.factor" split = c("rx.factor", "node4.factor") # Piped function to generate stratified crosstabs table colon_s %>% group_by(!!! syms(split)) %>% #Looks awkward, but avoids unquoted var names do( summary_factorlist(., dependent, explanatory, total = TRUE, p = TRUE) ) %>% data.frame() %>% dependent_label(colon_s, dependent, prefix = "") %>% colname2label(split)#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Warning: Chi-squared approximation may be incorrect#> Treatment >4 positive nodes Perforation No Yes #> 1 Obs No Age <40 years 14 (6.3) 0 (0.0) #> 2 Obs No 40-59 years 89 (40.3) 3 (42.9) #> 3 Obs No 60+ years 118 (53.4) 4 (57.1) #> 4 Obs No Sex Female 101 (45.7) 3 (42.9) #> 5 Obs No Male 120 (54.3) 4 (57.1) #> 6 Obs Yes Age <40 years 10 (11.8) 1 (50.0) #> 7 Obs Yes 40-59 years 31 (36.5) 1 (50.0) #> 8 Obs Yes 60+ years 44 (51.8) 0 (0.0) #> 9 Obs Yes Sex Female 44 (51.8) 1 (50.0) #> 10 Obs Yes Male 41 (48.2) 1 (50.0) #> 11 Lev No Age <40 years 14 (6.5) 0 (0.0) #> 12 Lev No 40-59 years 78 (36.3) 3 (50.0) #> 13 Lev No 60+ years 123 (57.2) 3 (50.0) #> 14 Lev No Sex Female 89 (41.4) 2 (33.3) #> 15 Lev No Male 126 (58.6) 4 (66.7) #> 16 Lev Yes Age <40 years 4 (4.7) 1 (25.0) #> 17 Lev Yes 40-59 years 33 (38.8) 1 (25.0) #> 18 Lev Yes 60+ years 48 (56.5) 2 (50.0) #> 19 Lev Yes Sex Female 39 (45.9) 3 (75.0) #> 20 Lev Yes Male 46 (54.1) 1 (25.0) #> 21 Lev+5FU No Age <40 years 15 (6.9) 0 (0.0) #> 22 Lev+5FU No 40-59 years 72 (33.2) 2 (25.0) #> 23 Lev+5FU No 60+ years 130 (59.9) 6 (75.0) #> 24 Lev+5FU No Sex Female 115 (53.0) 4 (50.0) #> 25 Lev+5FU No Male 102 (47.0) 4 (50.0) #> 26 Lev+5FU Yes Age <40 years 11 (13.9) <NA> #> 27 Lev+5FU Yes 40-59 years 31 (39.2) <NA> #> 28 Lev+5FU Yes 60+ years 37 (46.8) <NA> #> 29 Lev+5FU Yes Sex Female 44 (55.7) <NA> #> 30 Lev+5FU Yes Male 35 (44.3) <NA> #> Total p #> 1 14 (6.1) 0.790 #> 2 92 (40.4) #> 3 122 (53.5) #> 4 104 (45.6) 0.882 #> 5 124 (54.4) #> 6 11 (12.6) 0.183 #> 7 32 (36.8) #> 8 44 (50.6) #> 9 45 (51.7) 0.961 #> 10 42 (48.3) #> 11 14 (6.3) 0.689 #> 12 81 (36.7) #> 13 126 (57.0) #> 14 91 (41.2) 0.692 #> 15 130 (58.8) #> 16 5 (5.6) 0.221 #> 17 34 (38.2) #> 18 50 (56.2) #> 19 42 (47.2) 0.254 #> 20 47 (52.8) #> 21 15 (6.7) 0.606 #> 22 74 (32.9) #> 23 136 (60.4) #> 24 119 (52.9) 0.868 #> 25 106 (47.1) #> 26 11 (13.9) NA #> 27 31 (39.2) #> 28 37 (46.8) #> 29 44 (55.7) NA #> 30 35 (44.3)