Simulated data containing a Gaussian response variable y with two
covariates. The dataset was generated from a model with time-varying effects
of covariate x and the lagged value of the response variable, time-varying
intercept, and time-invariant effect of covariate z. The time-varying
coefficients vary according to a spline with 20 degrees of freedom.
Format
A data frame with 3000 rows and 5 variables:
- y
The response variable.
- x
A continuous covariate.
- z
A binary covariate.
- id
Variable defining individuals (1 to 50).
- time
Variable defining the time point of the measurement (1 to 30).
Source
The data was generated via gaussian_example.R in
https://github.com/ropensci/dynamite/tree/main/data-raw/