pitilde_by_chain {COMBO} | R Documentation |

## Compute the Mean Conditional Probability of Second-Stage Correct Classification, by First-Stage and True Outcome Across all Subjects for each MCMC Chain

### Description

Compute the Mean Conditional Probability of Second-Stage Correct Classification, by First-Stage and True Outcome Across all Subjects for each MCMC Chain

### Usage

```
pitilde_by_chain(n_chains, chains_list, V, n, 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 |

`V` |
A numeric design matrix. |

`n` |
An integer value specifying the number of observations in the sample.
This value should be equal to the number of rows of the design matrix, |

`n_cat` |
The number of categorical values that the true outcome, |

### Value

`pitilde_by_chain`

returns 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`

.
The first column contains the conditional probability `P( \tilde{Y} = 1 | Y^* = 1, Y = 1, V)`

.
The second column contains the conditional probability `P( \tilde{Y} = 2 | Y^* = 2, Y = 2, V)`

.

*COMBO*version 1.0.0 Index]