A dataset containing synthetic hospital admissions in the classic longitudinal format. The dataset counts imaginary 10 patients who undergo different (re)admission into a hospital. Some demographic and clinical variables are also included.
data.table with 53 rows and 12 variables:
Subject ID (integer)
Hospital admissions counter (integer)
Gender of patient (factor with 2 levels: "F" = females, "M" = males)
Age of patient in years at the given observation (integer)
Rehabilitation flag: if the admission has been in rehabilitation, then rehab = 1, else = 0 (integer)
Intensive Therapy flag: if the admission has been in intensive therapy, then it = 1, else = 0 (integer)
String which in one place marks the hospital admission types based on rehab and it. The standard admission is coded as "df" (default). If admission was in rehabilitation or in intensive therapy, rehab_it = "rehab" or "it", respectively (character)
Subject status at the end of the study. It takes 2 values: "alive" and "dead" (character)
Subject status at the end of the study. It takes 3 values: "alive" and "dead_in" and "dead_out" (character)
Exact admission date (date)
Exact discharge date (date)
Either censoring time or exact death time (date)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.