rstap-datasets.Rd
Small datasets for use in rstap examples and vignettes.
homog_longitudinal_bef_data
Simulated data for the longitudinal simulation
subj_ID
: The subject unique identifier
measure_ID
: The measurement unique identifier
bef_ID
The Built Environment Unique identifier
measure_date
The date at which the subject was measured
date_open
: The date at which the business opened
date_close
: The date at which the business may have closed; NA if the business is still open
date
: The date at which the subject first moved to the location associated with the distance and time with the built environment feature
class
: The kind of built environment feature. Only one is in the simulated dataset - "Coffee Shop"
dist
: The distance between the subject and BEF at the date to be associated with the measure ID
time
: The time for which the subject was "exposed" to the BEF at corresponding distance
homog_longitudinal_subject_data
subj_ID
: The subject unique identifier
Income
: Simulated continuous covariate
measure_date
: The simulated date the subject was measured
ran_int
: Random intercept generated for the longitudinal I simulation
y
: Continuous outcome simulated for longitudinal I simulation - meant to be akin to BMI
y_bern
: Bernoulli outcome simulated
sex
: Discrete 1-0 covariate simulated to be akin to sex
Coffee_Shop
: The "true" Coffee Shop Exposure covariate
centered_income
: scaled and centered version of Income covariate
centered_age
: scaled and centered version of Age covariate
homog_subject_data
subj_idThe subject unique identifier
yContinuous simulated outcome, meant to be BMI
sexdiscrete factor coded "M" for male, "F" for females
homog_distance_data
subj_id
: The subject unique identifier
BEF
Built Environment Feature class identifier - only one included in this dataset "Fast_Food"
Distance: The euclidean distance between the row's subject and Fast Food restaurant locations'