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Calculate summary statistics for demographics on a continuous variable

Source: R/by_strata_by_trt.R
demographics_continuous.Rd

Calculate a set of summary statistics (mean, median, sd, min, max, n_non_missing, n_missing) on a continuous variable for demographics endpoints.

Usage

demographics_continuous(dat, event_index, cell_index, subjectid_var, var, ...)

Arguments

dat

data.table. The analysis data set.

event_index

vector of integers that index the rows in dat that match the definition of an 'event'. Matching is done via the INDEX_ column in dat.

cell_index

A vector of integers referencing the rows of dat (as specified by the INDEX_ column in dat) that match the population to be analyzed. See the "Endpoint Events" vignette in ramnog for more information.

subjectid_var

character. Name of the subject identifier variable in the data (default is "USUBJID").

var

character. Name of the variable in the analysis data that is subject to the statistics.

...

Optional parameters.

Value

A data.table containing the summary statistics for the given continuous variable in the analysis data set.

Examples

dat <- data.table::data.table(
  USUBJID = c("S1", "S2", "S3", "S4"),
  AGE     = c(45, 52, 60, 38)
)
dat[, INDEX_ := .I]
#>    USUBJID   AGE INDEX_
#>     <char> <num>  <int>
#> 1:      S1    45      1
#> 2:      S2    52      2
#> 3:      S3    60      3
#> 4:      S4    38      4
data.table::setkey(dat, INDEX_)
demographics_continuous(dat, event_index = dat[["INDEX_"]],
                        cell_index = dat[["INDEX_"]],
                        subjectid_var = "USUBJID", var = "AGE")
#>            label  description qualifiers     value
#>           <char>       <char>     <char>     <num>
#> 1:          mean Demographics        AGE 48.750000
#> 2:        median Demographics        AGE 48.500000
#> 3:            sd Demographics        AGE  9.429563
#> 4:           min Demographics        AGE 38.000000
#> 5:           max Demographics        AGE 60.000000
#> 6: n_non_missing Demographics        AGE  4.000000
#> 7:     n_missing Demographics        AGE  0.000000