COMBO_EM_function function

EM-Algorithm Function for Estimation of the Misclassification Model

COMBO_EM_function(param_current, obs_Y_matrix, X, Z, sample_size, n_cat)

Arguments

• param_current: A numeric vector of regression parameters, in the order $\beta, \gamma$. The $\gamma$ vector is obtained from the matrix form. In matrix form, the gamma parameter matrix rows correspond to parameters for the Y* = 1

  observed outcome, with the dimensions of Z. In matrix form, the gamma parameter matrix columns correspond to the true outcome categories $j = 1, \dots,$ n_cat. The numeric vector gamma_v is obtained by concatenating the gamma matrix, i.e. gamma_v <- c(gamma_matrix).

• obs_Y_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.

• X: A numeric design matrix for the true outcome mechanism.

• Z: A numeric design matrix for the observation mechanism.

• 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 design matrix, X or Z.

• n_cat: The number of categorical values that the true outcome, Y, and the observed outcome, Y* can take.

Returns

COMBO_EM_function returns a numeric vector of updated parameter estimates from one iteration of the EM-algorithm.