COMBO_EM                EM-Algorithm Estimation of the Binary Outcome
                        Misclassification Model
COMBO_EM_2stage         EM-Algorithm Estimation of the Two-Stage Binary
                        Outcome Misclassification Model
COMBO_EM_data           Test data for the COMBO_EM function
COMBO_MCMC              MCMC Estimation of the Binary Outcome
                        Misclassification Model
COMBO_MCMC_2stage       MCMC Estimation of the Two-Stage Binary Outcome
                        Misclassification Model
COMBO_data              Generate Data to use in COMBO Functions
COMBO_data_2stage       Generate data to use in two-stage COMBO
                        Functions
LSAC_data               Example data from The Law School Admissions
                        Council's (LSAC) National Bar Passage Study
                        (Linda Wightman, 1998)
VPRAI_synthetic_data    Synthetic example data of pretrial failure risk
                        factors and outcomes, VPRAI recommendations,
                        and judge decisions
check_and_fix_chains    Check Assumption and Fix Label Switching if
                        Assumption is Broken for a List of MCMC Samples
check_and_fix_chains_2stage
                        Check Assumption and Fix Label Switching if
                        Assumption is Broken for a List of MCMC Samples
em_function             EM-Algorithm Function for Estimation of the
                        Misclassification Model
em_function_2stage      EM-Algorithm Function for Estimation of the
                        Two-Stage Misclassification Model
expit                   Expit function
jags_picker             Set up a Binary Outcome Misclassification
                        'jags.model' Object for a Given Prior
jags_picker_2stage      Set up a Two-Stage Binary Outcome
                        Misclassification 'jags.model' Object for a
                        Given Prior
label_switch            Fix Label Switching in MCMC Results from a
                        Binary Outcome Misclassification Model
label_switch_2stage     Fix Label Switching in MCMC Results from a
                        Binary Outcome Misclassification Model
loglik                  Expected Complete Data Log-Likelihood Function
                        for Estimation of the Misclassification Model
loglik_2stage           Expected Complete Data Log-Likelihood Function
                        for Estimation of the Two-Stage
                        Misclassification Model
mean_pistarjj_compute   Compute the Mean Conditional Probability of
                        Correct Classification, by True Outcome Across
                        all Subjects
misclassification_prob
                        Compute Conditional Probability of Each
                        Observed Outcome Given Each True Outcome, for
                        Every Subject
misclassification_prob2
                        Compute Conditional Probability of Each
                        Second-Stage Observed Outcome Given Each True
                        Outcome and First-Stage Observed Outcome, for
                        Every Subject
model_picker            Select a Binary Outcome Misclassification Model
                        for a Given Prior
model_picker_2stage     Select a Two-Stage Binary Outcome
                        Misclassification Model for a Given Prior
naive_jags_picker       Set up a Naive Logistic Regression 'jags.model'
                        Object for a Given Prior
naive_jags_picker_2stage
                        Set up a Naive Two-Stage Regression
                        'jags.model' Object for a Given Prior
naive_loglik_2stage     Observed Data Log-Likelihood Function for
                        Estimation of the Naive Two-Stage
                        Misclassification Model
naive_model_picker      Select a Logisitic Regression Model for a Given
                        Prior
naive_model_picker_2stage
                        Select a Naive Two-Stage Regression Model for a
                        Given Prior
perfect_sensitivity_EM
                        EM-Algorithm Estimation of the Binary Outcome
                        Misclassification Model while Assuming Perfect
                        Sensitivity
pi_compute              Compute Probability of Each True Outcome, for
                        Every Subject
pistar_by_chain         Compute the Mean Conditional Probability of
                        Correct Classification, by True Outcome Across
                        all Subjects for each MCMC Chain
pistar_by_chain_2stage
                        Compute the Mean Conditional Probability of
                        Correct Classification, by True Outcome Across
                        all Subjects for each MCMC Chain for a 2-stage
                        model
pistar_compute          Compute Conditional Probability of Each
                        Observed Outcome Given Each True Outcome, for
                        Every Subject
pistar_compute_for_chains
                        Compute Conditional Probability of Each
                        Observed Outcome Given Each True Outcome for a
                        given MCMC Chain, for Every Subject
pistar_compute_for_chains_2stage
                        Compute Conditional Probability of Each
                        Observed Outcome Given Each True Outcome for a
                        given MCMC Chain, for Every Subject for 2-stage
                        models
pitilde_by_chain        Compute the Mean Conditional Probability of
                        Second-Stage Correct Classification, by
                        First-Stage and True Outcome Across all
                        Subjects for each MCMC Chain
pitilde_compute         Compute Conditional Probability of Each
                        Second-Stage Observed Outcome Given Each True
                        Outcome and First-Stage Observed Outcome, for
                        Every Subject
pitilde_compute_for_chains
                        Compute Conditional Probability of Each
                        Observed Outcome Given Each True Outcome for a
                        given MCMC Chain, for Every Subject
q_beta_f                M-Step Expected Log-Likelihood with respect to
                        Beta
q_delta_f               M-Step Expected Log-Likelihood with respect to
                        Delta
q_gamma_f               M-Step Expected Log-Likelihood with respect to
                        Gamma
sum_every_n             Sum Every "n"th Element
sum_every_n1            Sum Every "n"th Element, then add 1
true_classification_prob
                        Compute Probability of Each True Outcome, for
                        Every Subject
w_j                     Compute E-step for Binary Outcome
                        Misclassification Model Estimated With the
                        EM-Algorithm
w_j_2stage              Compute E-step for Two-Stage Binary Outcome
                        Misclassification Model Estimated With the
                        EM-Algorithm
