Fix Label Switching in MCMC Results from a Binary Outcome Misclassification Model

Usage

label_switch_2stage(chain_matrix, dim_x, dim_z, dim_v, n_cat)

Arguments

chain_matrix: A numeric matrix containing the posterior samples for all parameters in a given MCMC chain. chain_matrix must be a named object (i.e. each parameter must be named as beta[j, p], gamma[k,j,p], or delta[l,k,j,p]).
dim_x: An integer specifying the number of columns of the design matrix of the true outcome mechanism, X.
dim_z: An integer specifying the number of columns of the design matrix of the first-stage observation mechanism, Z.
dim_v: An integer specifying the number of columns of the design matrix of the second-stage observation mechanism, V.
n_cat: An integer specifying the number of categorical values that the true outcome, \(Y\), the first-stage observed outcome, \(Y^*\), and the second-stage observed outcome \(\tilde{Y}\) can take.

Value

label_switch_2stage returns a named matrix of MCMC posterior samples for all parameters after performing label switching according the following pattern: all \(\beta\) terms are multiplied by -1, all \(\gamma\) and \(\delta\) terms are "swapped" with the opposite j index.