Create table of demographics statistics by most-likely latent subtype

Create table of demographics statistics by most-likely latent subtype

Usage

table_subtype_by_demographics(
  patient_data,
  subtype_and_stage_table,
  sust_data = bind_cols(patient_data, subtype_and_stage_table),
  footnotes_as_letters = FALSE,
  demographic_vars = c("CGG", "CGG 55-99", "Male", "Primary Race/Ethnicity"),
  ...
)

Arguments

patient_data

a data.frame

subtype_and_stage_table

a data.frame

sust_data

a data.frame combining patient_data and subtype_and_stage_table by cbind()

footnotes_as_letters

logical whether to convert footnote

demographic_vars

character varnames to compute statistics for symbols to letters (TRUE) instead of numbers (FALSE)

...

Arguments passed on to gtsummary::tbl_summary

data

(data.frame)
A data frame.

by

(tidy-select)
A single column from data. Summary statistics will be stratified by this variable. Default is NULL.

label

(formula-list-selector)
Used to override default labels in summary table, e.g. list(age = "Age, years"). The default for each variable is the column label attribute, attr(., 'label'). If no label has been set, the column name is used.

statistic

(formula-list-selector)
Specifies summary statistics to display for each variable. The default is list(all_continuous() ~ "{median} ({p25}, {p75})", all_categorical() ~ "{n} ({p}%)"). See below for details.

digits

(formula-list-selector)
Specifies how summary statistics are rounded. Values may be either integer(s) or function(s). If not specified, default formatting is assigned via assign_summary_digits(). See below for details.

type

(formula-list-selector)
Specifies the summary type. Accepted value are c("continuous", "continuous2", "categorical", "dichotomous"). If not specified, default type is assigned via assign_summary_type(). See below for details.

value

(formula-list-selector)
Specifies the level of a variable to display on a single row. The gtsummary type selectors, e.g. all_dichotomous(), cannot be used with this argument. Default is NULL. See below for details.

missing,missing_text,missing_stat

Arguments dictating how and if missing values are presented:

• missing: must be one of c("ifany", "no", "always").

• missing_text: string indicating text shown on missing row. Default is "Unknown".

• missing_stat: statistic to show on missing row. Default is "{N_miss}". Possible values are N_miss, N_obs, N_nonmiss, p_miss, p_nonmiss.

sort

(formula-list-selector)
Specifies sorting to perform for categorical variables. Values must be one of c("alphanumeric", "frequency"). Default is all_categorical(FALSE) ~ "alphanumeric".

percent

(string)
Indicates the type of percentage to return. Must be one of c("column", "row", "cell"). Default is "column".

In rarer cases, you may need to define/override the typical denominators. In these cases, pass an integer or a data frame. Refer to the ?cards::ard_categorical(denominator) help file for details.

include

(tidy-select)
Variables to include in the summary table. Default is everything().

Value

A gtsummary::tbl_summary

Examples

patient_data = sim_data |>
  dplyr::filter(.data$Category == "Patient")
table = sim_subtype_and_stage_table
table_subtype_by_demographics(patient_data, table,
  demographic_vars = "Sex")


  
Characteristic
      
Overall

N = 181
      
Subtype 1

N = 11
      
Subtype 3

N = 171
      
p-value
    
Sex, n (%)






1.0002
    Female
9 (50%)
1 (100%)
8 (47%)

    Male
9 (50%)
0 (0%)
9 (53%)

1 n (column %)
    
2 Group comparison was done by Fisher’s exact test