Description Usage Arguments Value Examples

Generate a stanfit object corresponding to a posterior distribution of corrected odds ratio given nondifferential misclassification that extends from the logit model but allows a random correlation between Sensitivity and Specificity.

1 2 3 4 5 |

`a` |
# of exposed subjects in the case group. |

`N1` |
# of total subjects in the case group. |

`c` |
# of exposed subjects in the control group. |

`N0` |
# of total subjects in the control group. |

`m.lg.se` |
normal distribution of logit Se with (mean = m.lg.se, sd = s.lg.se). |

`m.lg.sp` |
conditional normal distribution of logit Sp given Se with (m.lg.sp, s.lg.sp). |

`s.lg.se` |
standard deviation of logit Se |

`s.lg.sp` |
standard deviation of logit Sp |

`lg.se` |
used as an initial value for logit Se. Default to m.lg.se |

`lg.sp` |
used as an initial value for logit Sp. Default to m.lg.sp |

`m.z` |
normal distribution of Z with (mean = m.z, sd = s.z). |

`s.z` |
normal distribution of Z with (mean = m.z, sd = s.z). |

`z` |
used as an initial value of Fisher's Z transformed of rho, where correlation rho = (exp(2*z)-1)/(1+exp(2*z))). |

`name` |
a string of the name of the model. Default to "Logit Model with Random Correlation". |

`chains` |
number of Markov Chains. Default to 2. |

`traceplot` |
Logical, defaulting to |

`inc_warmup` |
Only evaluated when |

`window` |
Only evaluated when |

`refresh` |
an integer value used to control how often the progress of sampling is reported. By default, the progress indicator is turned off, thus refresh <= 0. If on, refresh = max(iter/10, 1) is generally recommended. |

`seed` |
the seed for random number generation. See stan for more details. |

`...` |
optional parameters passed to stan. |

It returns a stanfit object of this model, which inherits stanfit class methods. See here for more details.

1 2 3 4 5 6 7 8 9 10 | ```
# Case-control study data of Bipolar Disorder with rheumatoid arthritis (Farhi et al. 2016)
# Data from \url{https://www.sciencedirect.com/science/article/pii/S0165032715303864#bib13}
randCorrOR(a = 66, N1 = 11782, c = 243, N0 = 57973, m.lg.se = 1.069, m.lg.sp = 1.126,
s.lg.se = 0.893, s.lg.sp = 0.712, m.z = -0.399, s.z = 0.139, chains = 3,
iter = 10000, seed = 0)
randCorrOR(a = 66, N1 = 11782, c = 243, N0 = 57973, m.lg.se = 1.069, m.lg.sp = 1.126,
s.lg.se = 0.893, s.lg.sp = 0.712, lg.se = 2.197, lg.sp = 0.744, m.z = -0.399,
s.z = 0.139, traceplot = TRUE)
``` |

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