R/finalfit_internal_functions.R
ff_stratify_helper.RdHelp making stratified summary_factorlist tables
ff_stratify_helper(df.out, .data)Output from summary_factorlist
Original data frame used for summary_factorlist.
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
group_modify(~ summary_factorlist(.x, dependent, explanatory)) %>%
ff_stratify_helper(colon_s)
#> Treatment >4 positive nodes label levels No Yes
#> Obs No <40 years 14 (6.3) 0 (0.0)
#> Obs No 40-59 years 89 (40.3) 3 (42.9)
#> Obs No 60+ years 118 (53.4) 4 (57.1)
#> Obs No Female 101 (45.7) 3 (42.9)
#> Obs No Male 120 (54.3) 4 (57.1)
#> Obs Yes <40 years 10 (11.8) 1 (50.0)
#> Obs Yes 40-59 years 31 (36.5) 1 (50.0)
#> Obs Yes 60+ years 44 (51.8) 0 (0.0)
#> Obs Yes Female 44 (51.8) 1 (50.0)
#> Obs Yes Male 41 (48.2) 1 (50.0)
#> Lev No <40 years 14 (6.5) 0 (0.0)
#> Lev No 40-59 years 78 (36.3) 3 (50.0)
#> Lev No 60+ years 123 (57.2) 3 (50.0)
#> Lev No Female 89 (41.4) 2 (33.3)
#> Lev No Male 126 (58.6) 4 (66.7)
#> Lev Yes <40 years 4 (4.7) 1 (25.0)
#> Lev Yes 40-59 years 33 (38.8) 1 (25.0)
#> Lev Yes 60+ years 48 (56.5) 2 (50.0)
#> Lev Yes Female 39 (45.9) 3 (75.0)
#> Lev Yes Male 46 (54.1) 1 (25.0)
#> Lev+5FU No <40 years 15 (6.9) 0 (0.0)
#> Lev+5FU No 40-59 years 72 (33.2) 2 (25.0)
#> Lev+5FU No 60+ years 130 (59.9) 6 (75.0)
#> Lev+5FU No Female 115 (53.0) 4 (50.0)
#> Lev+5FU No Male 102 (47.0) 4 (50.0)
#> Lev+5FU Yes <40 years 11 (13.9) 0 (NaN)
#> Lev+5FU Yes 40-59 years 31 (39.2) 0 (NaN)
#> Lev+5FU Yes 60+ years 37 (46.8) 0 (NaN)
#> Lev+5FU Yes Female 44 (55.7) 0 (NaN)
#> Lev+5FU Yes Male 35 (44.3) 0 (NaN)