rstap-datasets.RdSmall datasets for use in rstap examples and vignettes.
homog_longitudinal_bef_dataSimulated 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_datasubj_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_datasubj_idThe subject unique identifier
yContinuous simulated outcome, meant to be BMI
sexdiscrete factor coded "M" for male, "F" for females
homog_distance_datasubj_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'