Description Usage Arguments Value See Also
This function prints basic summary measurements for posterior distributions of cluster-
level prevalences across all time periods considered. It does so by examining the
object output by the EpiBayes_ns
or EpiBayes_s
function
of class eb
.
1 2 |
x |
An object of class |
... |
Additional arguments to be passed on to summary. |
The summary statistics are returned in a list with the first entry containing the
simulation output (p2.tilde
, p4.tilde
, and p6.tilde
), the next
containing summary measures for the first ten replicated data sets' gam
, and
the rest containing summary measures for the first ten replicated data sets'
tau
values (one for each subzone, if applicable).
The summary measurements taken on the posterior distributions include the posterior
mean, standard deviation, standard error of the mean, time-series adjusted standard
error of the mean, and the lower and upper HPD interval limits, in that order.
For reference purposes, below are the descriptions for the summarized variables.
By default, the function returns summary values for up to ten replicated data sets of
gam
and tau
and reports 95
Output | Description |
p2.tilde | Proportion of simulated data sets that result in the probability of poi prevalence below poi.thresh with probability p1 |
p4.tilde | Proportion of simulated data sets that result in the probability of poi prevalence above poi.thresh with probability p1 |
p6.tilde | Proportion of simulated data sets that result in the probability of poi prevalence between poi.lb and poi.ub with probability p1 |
taumat | Posterior distributions of the cluster-level prevalence for all simulated data sets (i.e., reps ) |
gammat | Posterior distribution of the subzone-level prevalence (3-level) OR Posterior distribution of the probability of the disease being in the region (2-level) |
This is a method for objects of class eb
returned by the function
EpiBayes_ns
or EpiBayes_s
. The summary
method for
the eb
object class allows for customization of this output.
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