simul1: Simulated data set
Description
The simulated data set simul1 considers a situation with four
binary covariates in both sub-models of the Pogit model,
i.e. X = W.
The respective design matrix is built by computing all 2^4 possible 0/1
combinations and one observation is generated for each covariate pattern.
The regression effects are set to beta = {0.75,0.5,-2,0,0} in the
Poisson and to alpha = {2.2,-1.9,0,0,0} in the logit model.
Additionally to the main study sample, validation data are available for
each covariate pattern. For details concerning the simulation setup, see
Dvorzak and Wagner (2016).
Format
A data frame with 16 rows and the following 9 variables:
y- number of observed counts for each covariate pattern
E- total exposure time
X.0- intercept
X.1, X.2, X.3, X.4- binary covariates
v- number of reported cases for each covariate pattern in
the validation sample
m- number of true cases subject to the fallible reporting
process (sample size of validation data)