simul2: Simulated data set
Description
The simulated data set simul2 considers a situation with clustered
observations and 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. C=50 clusters are built containing
one unit with each of the resulting 16 covariate patterns, i.e. a total of
I=800 units. The regression effects are set to beta = {0.75,0.1,0.1,0,0}
in the Poisson and to alpha = {2.2,-0.3,0,-0.3,0} in the logit model.
Random intercepts in both sub-models are simulated from a normal distribution
with standard deviations $\theta_\beta$=0.1 and
$\theta_\alpha$=0.3. Additionally to the main study sample,
validation data are available for each covariate pattern and cluster.
For details concerning the simulation setup, see Dvorzak and Wagner (2016).
Format
A data frame with 800 rows and the following 10 variables:
y- number of observed counts for each covariate pattern
in each cluster
E- total exposure times for each unit
cID- cluster ID for each unit
X.0- intercept
X.1, X.2, X.3, X.4- binary covariates
v- number of reported cases for each covariate pattern in each
cluster in the validation sample
m- number of true cases subject to the fallible reporting
process (sample size of validation data)