Generate sample data with a nominal treatment for ps_nominal() examples

Produces a synthetic data frame with a four-level nominal treatment variable (rtyp: tricuspid repair types COS, PER, DEV, CE), mimicking the dataset used in tp.lm.logistic_propensity.polytomous.sas.

Usage

sample_ps_data_nominal(n = 200L, seed = 42L)

Arguments

n

Number of patients per treatment level. Total rows = 4 * n. Default 200L.

seed

Random seed. Default 42L. The fixed default gives the same demo dataset on every call. NULL draws from the caller's random-number stream, as ps_match() does: the data differ from call to call, and set.seed() before the call reproduces them. A negative seed gives the same data as its absolute value.

Value

A data frame with 4 * n rows and columns: id, rtyp (unordered factor), age, female, ef, diabetes, hypertension.

See also

ps_nominal()

Examples

dta <- sample_ps_data_nominal(n = 100, seed = 7)
table(dta$rtyp)
#> 
#> COS PER DEV  CE 
#> 100 100 100 100 
str(dta)
#> 'data.frame':	400 obs. of  7 variables:
#>  $ id          : int  1 2 3 4 5 6 7 8 9 10 ...
#>  $ rtyp        : Factor w/ 4 levels "COS","PER","DEV",..: 1 1 1 1 1 1 1 1 1 1 ...
#>  $ age         : num  80.9 46 51.1 53.9 48.3 ...
#>  $ female      : int  0 0 0 1 1 0 1 1 0 1 ...
#>  $ ef          : num  52.8 65.9 47.8 54.1 62.1 ...
#>  $ diabetes    : int  0 0 0 0 0 0 0 0 0 0 ...
#>  $ hypertension: int  1 0 0 1 1 1 0 1 0 1 ...