COMBO_weight function

Compute E-step for Binary Outcome Misclassification Model Estimated With the EM-Algorithm

COMBO_weight(ystar_matrix, pistar_matrix, pi_matrix, sample_size, n_cat)

Arguments

• ystar_matrix: A numeric matrix of indicator variables (0, 1) for the observed outcome Y*. Rows of the matrix correspond to each subject. Columns of the matrix correspond to each observed outcome category. Each row should contain exactly one 0 entry and exactly one 1 entry.
• pistar_matrix: A numeric matrix of conditional probabilities obtained from the internal function pistar_compute. Rows of the matrix correspond to each subject and to each observed outcome category. Columns of the matrix correspond to each true, latent outcome category.
• pi_matrix: A numeric matrix of probabilities obtained from the internal function pi_compute. Rows of the matrix correspond to each subject. Columns of the matrix correspond to each true, latent outcome category.
• sample_size: An integer value specifying the number of observations in the sample. This value should be equal to the number of rows of the observed outcome matrix, ystar_matrix.
• n_cat: The number of categorical values that the true outcome, Y, and the observed outcome, Y*, can take.

Returns

COMBO_weight returns a matrix of E-step weights for the EM-algorithm, computed as follows: $\sum_{k = 1}^2 \frac{y^*_{ik} \pi^*_{ikj} \pi_{ij}}{\sum_{\ell = 1}^2 \pi^*_{i k \ell} \pi_{i \ell}}$. Rows of the matrix correspond to each subject. Columns of the matrix correspond to the true outcome categories $j = 1, \dots,$ n_cat.