| diab_df {chest} | R Documentation |
Example data: Health outcomes of 2372 adults with and without diabetes
Description
A data frame with 2372 rows and 14 variables with diabetes status
diabetes and mortality status endpoint. For the purpose
of demonstrate, assume that we are interested in the association
between diabetes and endpoint. Other variables are
considered as possible confounders. The purposes of this dataset
is to illustrate those functions in chest package only. Therefore,
we assume it is a cohort design for Cox Proportional Hazard regression,
and a case-control design for logistic regression.
Usage
diab_df
Format
A data frame with 2372 rows and 14 variables:
- Diabetes
diabetes status 1: with diabetes 0: without diabetes
- Endpoint
mortality status 1: reached end point, and 0: survived
- Age
Age, in years
- Sex
sex, 1: male, 2: Female
- BMI
Body mass index
- Married
marital status 1: married, 0: not
- Smoke
smoking status 1: smoker, 0: non-smoker
- CVD
cardiovascular disease 1: yes 0: no
- Cancer
cancer 1: yes, 0: no
- Education
education 1: high, 0: low
- Income
income 1: high, 0: low
- t0
time (age) at the start of the follow-up
- t1
time (age) at the end of the follow-up
- mid
matched set id, for conditional logistic regression