pitilde_compute {COMBO} | R Documentation |
Compute Conditional Probability of Each Second-Stage Observed Outcome Given Each True Outcome and First-Stage Observed Outcome, for Every Subject
pitilde_compute(delta, V, n, n_cat)
delta |
A numeric array of regression parameters for the second-stage observed
outcome mechanism, |
V |
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, |
pitilde_compute
returns an array of conditional probabilities,
P(\tilde{Y}_i = \ell | Y^*_i = k, Y_i = j, V_i) = \frac{\text{exp}\{\delta_{\ell kj0} + \delta_{\ell kjV} V_i\}}{1 + \text{exp}\{\delta_{\ell kj0} + \delta_{\ell kjV} V_i\}}
for each of the i = 1, \dots,
n
subjects. Rows of the matrix
correspond to each subject and second-stage observed outcome. Specifically, the probability
for subject i
and observed category $1$ occurs at row i
. The probability
for subject i
and observed category $2$ occurs at row i +
n
.
Columns of the matrix correspond to the first-stage outcome categories, k = 1, \dots,
n_cat
.
The third dimension of the array corresponds to the true outcome categories,
j = 1, \dots,
n_cat
.