This is a subfunction of `cluster_gen` that performs cluster sampling, with the twist that each cluster level has its own questionnaire.
cluster_gen_separate(
n_levels,
n,
N,
sum_pop,
calc_weights,
sampling_method,
cluster_labels,
resp_labels,
collapse,
n_X,
n_W,
cat_prop,
c_mean,
sigma,
cor_matrix,
rho,
theta,
whitelist,
verbose,
...
)number of cluster levels
numeric vector with the number of sampled observations (clusters or subjects) on each level
list of numeric vector with the population size of each *sampled* cluster element on each level
total population at the lowest level (sampled or not)
if `TRUE`, sampling weights are calculated
can be "SRS" for Simple Random Sampling or "PPS" for Probabilities Proportional to Size, "mixed" to use SRS for students and PPS otherwise or a vector with the sampling method for each level
character vector with the names of each cluster level
character vector with the names of the questionnaire respondents on each level
if `TRUE`, function output contains only one data frame with all answers
list of `n_X` per cluster level
list of `n_W` per cluster level
list of cumulative proportions for each item. If theta
= TRUE, the first element of cat_prop must be a scalar 1, which
corresponds to the theta.
vector of means for the continuous variables or list of vectors for the continuous variables for each level
vector of standard deviations for the continuous variables or list of vectors for the continuous variables for each level
Correlation matrix between all variables (except weights)
estimated intraclass correlation
if TRUE, the first continuous variable will be labeled
'theta'. Otherwise, it will be labeled 'q1'.
used when `n = select(...)`, determines which PSUs get to generate questionnaires
if `TRUE`, prints output messages
Additional parameters to be passed to `questionnaire_gen()`
cluster_gen cluster_gen_together