Unlike prediction type, the distribution of posterior probabilities
by comparison type shows distinct differences (Fig.
The LCA classes were given the following descriptive labels based on observed VA utilization: (1) Low VA medical use with minimal VA medication and mental health use (representing an expected 43 percent of patients based on posterior probabilities
from the LCA model; 45.4 percent based on assigning patients to the most probable class); (2) Low VA medical users with significant VA medication and mental health use (12.7 percent mean posterior probability); (3) Moderate VA medical use with minimalVA medication and mental health use (23.1 percent); (4) Moderate VA medical use with significant VA medication and mental health use (10.5 percent); and (5) High use of all VA services including inpatient hospitalizations (10.8 percent).
As noted earlier, it may be that subjects incorrectly assess .50:.50 posterior probabilities
over the remaining states, rather than 2/3: 1/3 win probabilities for Switch versus Stay, and that our Merge treatment will help overcome that updating error.
Assignment of individuals to classes involves the use of the posterior probabilities
of class membership for each student, which here would be four values capturing the probability of the student's membership in each of the four classes.
Exact distribution Approximation Beta (2,1) N(1,[infinity]) Beta(1,2) N(0, [infinity]) Beta (10,10) N(0.5000,8.4853) Beta (5,1) N(1, [infinity]) Beta(1,5) N(0, [infinity]) Beta (2,2) N(0.5000,2.8284) Beta (3,3) N(0.5000,4.0) Beta (2,4) N(0.2500,4.6188) Beta (4,4) N(0.5000,4.8990) Beta (5,5) N(1,5.6569) Beta(30, 20) N(0.6042,14.1673) Beta (20,30) N(0.3958,14.1673) Beta(50, 20) N(0.7206,18.3776) Beta (20,50) N(0.2794,18.3776) Table 2: Posterior probabilities
and Bayes factor.
However, we also use the SUCRA and posterior probabilities
of outcomes to distinguish the subtle differences among six treatments.
Two major clades supported by posterior probabilities
of 1.00 and 0.97, respectively (Fig.
After the local fusion was executed on all of the training sets, the posterior probabilities
were calculated for each signal type, for each training set.
Phylogeographic reconstruction identified a specific location for the root of the tree with posterior probabilities
for state sp = 0.81 for the locality of China (Supplementary Material Figure S2).
The computations of the posterior probabilities
for different modes considering historical data only are presented first, and, the approach is extended to incorporate process knowledge in Section 5.
A deer with an eye lens dry mass of 0.370 g had posterior probabilities
of 0.33 and 0.67 of being in the yearling and prime-age classes, respectively.