Correcting Misclassified Binary Outcomes in Association Studies


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Documentation for package ‘COMBO’ version 1.0.0

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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
COMBO_data Generate Data to use in COMBO Functions
COMBO_data_2stage Generate Data to use in two-stage COMBO Functions
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_MCMC MCMC Estimation of the Binary Outcome Misclassification Model
COMBO_MCMC_2stage MCMC Estimation of the Two-Stage Binary Outcome Misclassification Model
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
pistar_by_chain Compute the Mean Conditional Probability of Correct Classification, by True Outcome Across all Subjects for each MCMC Chain
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
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
pi_compute Compute Probability of Each True Outcome, 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