Function to simulate data from a relevant data generating process (DGP) ; currently this function supports the creation of DGPs with 1 layer of area effects (i.e. small-area effects)
Usage
dgf(
n.sims = 1,
n = 100,
pi.hat.naive = 0.5,
p = 1,
X_corr = 0,
pi = 0.05,
Moran.I.corr = 0.8,
spatial_structure = "scotland_lipcancer"
)Arguments
- n.sims
how many samples of simulated data would you like?;
- n
how large (sample size) should each sample be?;
- pi.hat.naive
what should be the fraction of cases in the sample?;
- p
how many normally-distributed covariates should the DGP have?;
- X_corr
what should be the average correlation among these covariates?;
- pi
what is the population-level probability of sampling a case?
- Moran.I.corr
what degree of global spatial autocorrelation (Moran I) should the underlying DGP have?;
- spatial_structure
on which map should the data be simulated ? (scotland_lipcancer, pennsylvania_lungcancer, and newyork_leukemia)