rmultinom6dVineCopulaREMADA {CopulaREMADA} | R Documentation |

## Simulation from multinomial six-variate 1-truncated D-vine copula mixed models for meta-analysis of two diagnostic tests accounting for within and between studies dependence

### Description

Simulation from multinomial six-variate 1-truncated D-vine copula mixed models for meta-analysis of two diagnostic tests accounting for within and between studies dependence

### Usage

```
rmultinom6dVineCopulaREMADA.norm(N,p,si,taus,qcond,tau2par)
rmultinom6dVineCopulaREMADA.beta(N,p,g,taus,qcond,tau2par)
```

### Arguments

`N` |
sample size |

`p` |
Vector |

`si` |
Vector |

`g` |
Vector |

`taus` |
Kendall's tau values |

`qcond` |
function for the inverse conditional copula cdf |

`tau2par` |
function for maping Kendall's taus to copula parameters |

### Value

Simulated data with 8 columns and `N`

rows.

- y001
the number of the test results in the diseased where the test 1 outcome is negative and the test 2 outcome is negative

- y011
the number of the test results in the diseased where the test 1 outcome is negative and the test 2 outcome is positive

- y101
the number of the test results in the diseased where the test 1 outcome is positive and the test 2 outcome is negative

- y111
the number of the test results in the diseased where the test 1 outcome is positive and the test 2 outcome is positive

- y000
the number of the test results in the non-diseased where the test 1 outcome is negative and the test 2 outcome is negative

- y010
the number of the test results in the non-diseased where the test 1 outcome is negative and the test 2 outcome is positive

- y100
the number of the test results in the non-diseased where the test 1 outcome is positive and the test 2 outcome is negative

- y110
the number of the test results in the non-diseased where the test 1 outcome is positive and the test 2 outcome is positive

### References

Nikoloulopoulos, A.K. (2024) Joint meta-analysis of two diagnostic tests accounting for within and between studies dependence. Submitted.

### See Also

### Examples

```
N=11
p=c(0.03667409, 0.09299767, 0.29450436, 0.01733081, 0.04923809, 0.02984361)
si=c(1.69868880, 0.54292079, 0.58489574, 0.92918177, 0.48998484, 0.57004098)
taus=c(-0.52475006, 0.55768873, 0.18454559, 0.02233204, 0.57570506)
tau2par=tau2par.bvn
qcond=qcondbvn
out=rmultinom6dVineCopulaREMADA.norm(N,p,si,taus,qcond,tau2par)
y101=out[,1]
y011=out[,2]
y111=out[,3]
y001=out[,4]
y100=out[,5]
y010=out[,6]
y110=out[,7]
y000=out[,8]
```

*CopulaREMADA*version 1.6.2 Index]