Check Assumption and Fix Label Switching if Assumption is Broken for a List of MCMC Samples

Usage

check_and_fix_chains_2stage(
  n_chains,
  chains_list,
  pistarjj_matrix,
  pitildejjj_matrix,
  dim_x,
  dim_z,
  dim_v,
  n_cat
)

Arguments

n_chains: An integer specifying the number of MCMC chains to compute over.
chains_list: A numeric list containing the samples from n_chains MCMC chains.
pistarjj_matrix: A numeric matrix of the average conditional probability \(P(Y^* = j | Y = j, Z)\) across all subjects for each MCMC chain, obtained from the pistar_by_chain function.
pitildejjj_matrix: A numeric matrix of the average conditional probability \(P( \tilde{Y} = j | Y^* = j, Y = j, V)\) across all subjects for each MCMC chain. Rows of the matrix correspond to MCMC chains, up to n_chains. Obtained from the pitilde_by_chain function.
dim_x: The number of columns of the design matrix of the true outcome mechanism, X.
dim_z: The number of columns of the design matrix of the first-stage observation mechanism, Z.
dim_v: The number of columns of the design matrix of the second-stage observation mechanism, V.
n_cat: The number of categorical values that the true outcome, Y, and the observed outcome, Y* can take.

Value

check_and_fix_chains returns a numeric list of the samples from n_chains MCMC chains which have been corrected for label switching if the following assumption is not met: \(P(Y^* = j | Y = j, Z) > 0.50 \forall j\).