pistar_compute_for_chains {COMBO} | R Documentation |
Compute Conditional Probability of Each Observed Outcome Given Each True Outcome for a given MCMC Chain, for Every Subject
pistar_compute_for_chains(chain_colMeans, Z, n, n_cat)
chain_colMeans |
A numeric vector containing the posterior means for all
sampled parameters in a given MCMC chain. |
Z |
A numeric design matrix. |
n |
An integer value specifying the number of observations in the sample.
This value should be equal to the number of rows of the design matrix, |
n_cat |
The number of categorical values that the true outcome, |
pistar_compute_for_chains
returns a matrix of conditional probabilities,
P(Y_i^* = k | Y_i = j, Z_i) = \frac{\text{exp}\{\gamma_{kj0} + \gamma_{kjZ} Z_i\}}{1 + \text{exp}\{\gamma_{kj0} + \gamma_{kjZ} Z_i\}}
for each of the i = 1, \dots,
n
subjects. Rows of the matrix
correspond to each subject and observed outcome. Specifically, the probability
for subject i
and observed category $0$ occurs at row i
. The probability
for subject i
and observed category $1$ occurs at row i +
n
.
Columns of the matrix correspond to the true outcome categories j = 1, \dots,
n_cat
.