Create table of demographics statistics by most-likely latent subtype
Source:R/table_subtype_by_demographics.R
table_subtype_by_demographics.RdCreate table of demographics statistics by most-likely latent subtype
Arguments
- patient_data
- subtype_and_stage_table
- sust_data
a data.frame combining
patient_dataandsubtype_and_stage_tablebycbind()- 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_summarydata(
data.frame)
A data frame.by(
tidy-select)
A single column fromdata. Summary statistics will be stratified by this variable. Default isNULL.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 islist(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 viaassign_summary_digits(). See below for details.type(
formula-list-selector)
Specifies the summary type. Accepted value arec("continuous", "continuous2", "categorical", "dichotomous"). If not specified, default type is assigned viaassign_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 isNULL. See below for details.missing,missing_text,missing_statArguments dictating how and if missing values are presented:
missing: must be one ofc("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 areN_miss,N_obs,N_nonmiss,p_miss,p_nonmiss.
sort(
formula-list-selector)
Specifies sorting to perform for categorical variables. Values must be one ofc("alphanumeric", "frequency"). Default isall_categorical(FALSE) ~ "alphanumeric".percent(
string)
Indicates the type of percentage to return. Must be one ofc("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_tabulate(denominator)help file for details.include(
tidy-select)
Variables to include in the summary table. Default iseverything().
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
1 n (column %)
2 Group comparison was done by Fisher’s exact test