COMBO1.2.0 package

Correcting Misclassified Binary Outcomes in Association Studies

Check Assumption and Fix Label Switching if Assumption is Broken for a...

Check Assumption and Fix Label Switching if Assumption is Broken for a...

Generate data to use in two-stage COMBO Functions

Generate Data to use in COMBO Functions

EM-Algorithm Estimation of the Two-Stage Binary Outcome Misclassificat...

EM-Algorithm Estimation of the Binary Outcome Misclassification Model

MCMC Estimation of the Two-Stage Binary Outcome Misclassification Mode...

MCMC Estimation of the Binary Outcome Misclassification Model

EM-Algorithm Function for Estimation of the Two-Stage Misclassificatio...

EM-Algorithm Function for Estimation of the Misclassification Model

Expit function

Set up a Two-Stage Binary Outcome Misclassification `jags.model`

Objec...

Set up a Binary Outcome Misclassification `jags.model`

Object for a Gi...

Fix Label Switching in MCMC Results from a Binary Outcome Misclassific...

Fix Label Switching in MCMC Results from a Binary Outcome Misclassific...

Expected Complete Data Log-Likelihood Function for Estimation of the T...

Expected Complete Data Log-Likelihood Function for Estimation of the M...

Compute the Mean Conditional Probability of Correct Classification, by...

Compute Conditional Probability of Each Observed Outcome Given Each Tr...

Compute Conditional Probability of Each Second-Stage Observed Outcome ...

Select a Two-Stage Binary Outcome Misclassification Model for a Given ...

Select a Binary Outcome Misclassification Model for a Given Prior

Set up a Naive Two-Stage Regression `jags.model`

Object for a Given Pr...

Set up a Naive Logistic Regression `jags.model`

Object for a Given Pri...

Observed Data Log-Likelihood Function for Estimation of the Naive Two-...

Select a Naive Two-Stage Regression Model for a Given Prior

Select a Logisitic Regression Model for a Given Prior

EM-Algorithm Estimation of the Binary Outcome Misclassification Model ...

Compute Probability of Each True Outcome, for Every Subject

Compute the Mean Conditional Probability of Correct Classification, by...

Compute the Mean Conditional Probability of Correct Classification, by...

Compute Conditional Probability of Each Observed Outcome Given Each Tr...

Compute Conditional Probability of Each Observed Outcome Given Each Tr...

Compute Conditional Probability of Each Observed Outcome Given Each Tr...

Compute the Mean Conditional Probability of Second-Stage Correct Class...

Compute Conditional Probability of Each Observed Outcome Given Each Tr...

Compute Conditional Probability of Each Second-Stage Observed Outcome ...

M-Step Expected Log-Likelihood with respect to Beta

M-Step Expected Log-Likelihood with respect to Delta

M-Step Expected Log-Likelihood with respect to Gamma

Sum Every "n"th Element

Sum Every "n"th Element, then add 1

Compute Probability of Each True Outcome, for Every Subject

Compute E-step for Two-Stage Binary Outcome Misclassification Model Es...

Compute E-step for Binary Outcome Misclassification Model Estimated Wi...

Use frequentist and Bayesian methods to estimate parameters from a binary outcome misclassification model. These methods correct for the problem of "label switching" by assuming that the sum of outcome sensitivity and specificity is at least 1. A description of the analysis methods is available in Hochstedler and Wells (2023) <doi:10.48550/arXiv.2303.10215>.

Maintainer: Kimberly Hochstedler Webb License: MIT + file LICENSE Last published: 2024-10-30