Description Usage Arguments Details Value Author(s) See Also Examples

Given the frequencies of true positives, false negative, false positives and true negatives from primary diagnostic studies `madad`

calculates various summary statistics. Apart from sensitivities, specificities and false positive rates the function also calculates the diagnostic odds ratio (DOR) and the positve and negative likelihood ratios, together with their respective confidence intervals. Also two hypothesis tests are calculated: one testing the equality of the sensitivities and the same for the false positive rates.

1 2 3 4 5 6 |

`x` |
any object that can be converted to a data frame with integer variables |

`TP` |
vector of integers, ingored if |

`FN` |
vector of integers, ingored if |

`FP` |
vector of integers, ingored if |

`TN` |
vector of integers, ingored if |

`correction` |
numeric, continuity correction applied to zero cells. |

`correction.control` |
character, if set to |

`level` |
numeric, confidence level for the calculations of confidence intervals. |

`method` |
character, method used to calculate the confidence intervals for sensitivities, specificities and false positive rates. One of |

`yates` |
logical, should a Yates correction be used for testing the equality of sensitivities and specificities? |

`digits` |
integer, to what decimal place is the output to be rounded? |

`suppress` |
logical, suppress the warning that is generated by |

`...` |
further arguments to be passed on the other funtions (currently none). |

All calculations are performed using the continuity corrected cell counts, so if there are zero cells, the sensitivities and specificities not equal to 1. This can be avoided by setting `correction.control`

to `"none"`

.

The test for the equality of sensitivities and its counterpart for the specificities is based on `prop.test`

. This function will occasionally output warnings.

An object of class `madad`

which is essentially a list with the following components:

`sens` |
A list of two components, |

`spec` |
A list of two components, |

`fpr` |
A list of two components, |

`sens.htest` |
An object of class |

`spec.htest` |
An object of class |

`DOR` |
A list of two components, |

`posLR` |
A list of two components, |

`negLR` |
A list of two components, |

`cor_sens_fpr` |
numeric, the correlation of the sensitivities and false-positive rates. |

`level` |
numeric |

`method` |
character |

`names` |
character vector, if the main argument of |

`nobs` |
integer, number of primary studies. |

`data` |
data frame, with columns |

`data.name` |
character, name of the main argument. |

`correction` |
numeric |

`correction.control` |
character |

Philipp Doebler <[email protected]>

1 2 3 |

```
Loading required package: mvtnorm
Loading required package: ellipse
Loading required package: mvmeta
This is mvmeta 0.4.7. For an overview type: help('mvmeta-package').
Descriptive summary of AuditC with 14 primary studies.
Confidence level for all calculations set to 95 %
Using a continuity correction of 0.5 if applicable
Diagnostic accuracies
sens 2.5% 97.5% spec 2.5% 97.5%
[1,] 0.83 0.72 0.91 0.88 0.86 0.90
[2,] 0.71 0.64 0.77 0.85 0.83 0.87
[3,] 0.65 0.47 0.79 0.94 0.90 0.96
[4,] 0.91 0.79 0.97 0.78 0.73 0.82
[5,] 0.87 0.81 0.91 0.82 0.80 0.84
[6,] 0.97 0.91 0.99 0.57 0.49 0.64
[7,] 0.99 0.93 1.00 0.79 0.75 0.82
[8,] 1.00 0.99 1.00 0.48 0.47 0.49
[9,] 0.92 0.82 0.96 0.71 0.64 0.77
[10,] 0.74 0.67 0.80 0.83 0.82 0.84
[11,] 0.85 0.79 0.90 0.77 0.73 0.81
[12,] 0.94 0.85 0.98 0.81 0.77 0.84
[13,] 0.96 0.84 0.99 0.72 0.62 0.81
[14,] 0.75 0.68 0.80 0.75 0.70 0.79
Test for equality of sensitivities:
X-squared = 272.3603, df = 13, p-value = <2e-16
Test for equality of specificities:
X-squared = 2204.8, df = 13, p-value = <2e-16
Diagnostic OR and likelihood ratios
DOR 2.5% 97.5% posLR 2.5% 97.5% negLR 2.5% 97.5%
[1,] 36.38 17.59 75.25 6.90 5.56 8.56 0.19 0.11 0.34
[2,] 13.91 9.82 19.72 4.74 4.10 5.47 0.34 0.27 0.43
[3,] 28.60 11.13 73.47 10.66 5.86 19.38 0.37 0.23 0.61
[4,] 36.73 11.93 113.14 4.13 3.32 5.13 0.11 0.04 0.31
[5,] 30.36 18.44 49.99 4.82 4.20 5.52 0.16 0.10 0.24
[6,] 44.16 12.08 161.49 2.24 1.87 2.69 0.05 0.01 0.17
[7,] 515.73 31.69 8393.76 4.73 4.01 5.58 0.01 0.00 0.15
[8,] 1388.85 86.75 22234.71 1.92 1.88 1.97 0.00 0.00 0.02
[9,] 26.61 10.52 67.27 3.17 2.51 4.00 0.12 0.05 0.27
[10,] 13.77 9.87 19.22 4.34 3.88 4.86 0.32 0.25 0.40
[11,] 18.72 11.57 30.27 3.68 3.08 4.40 0.20 0.14 0.28
[12,] 69.44 23.11 208.65 4.93 4.10 5.92 0.07 0.03 0.20
[13,] 60.44 10.95 333.68 3.48 2.41 5.01 0.06 0.01 0.28
[14,] 8.85 5.95 13.16 2.98 2.45 3.63 0.34 0.26 0.43
Correlation of sensitivities and false positive rates:
rho 2.5 % 97.5 %
0.68 0.23 0.89
```

mada documentation built on May 31, 2017, 3:05 a.m.

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