meta-transf | R Documentation |

Auxiliary functions to (back) transform effect estimates or confidence / prediction interval limit(s).

```
transf(x, sm, func = NULL, args = NULL)
cor2z(x)
p2asin(x)
p2logit(x)
VE2logVR(x)
backtransf(x, sm, n, time, func = NULL, args = NULL)
asin2ir(x, time = NULL)
asin2p(x, n = NULL)
logit2p(x)
logVR2VE(x)
z2cor(x)
```

`x` |
Numerical vector with effect estimates, lower or upper confidence / prediction interval limit(s). |

`sm` |
Summary measure. |

`func` |
User-specified function for (back) transformation. |

`args` |
Function arguments for user-specified function. |

`n` |
Sample size(s) to back transform Freeman-Tukey transformed proportions. |

`time` |
Time(s) to back transform Freeman-Tukey transformed incidence rates. |

Often in a meta-analysis, effect estimates are transformed before
calculating a weighted average. For example, the log odds ratio and
its standard error is used instead of the odds ratio in R function
`metagen`

. To report the results of a meta-analysis,
effect estimates are typically back transformed to the original
scale. R package **meta** provides some auxiliary functions for
(back) transformations.

The following auxiliary functions are provided by R package
**meta** to transform effect estimates or confidence /
prediction interval limits.

Function | Transformation |

`cor2z` | Correlations to Fisher's Z transformed correlations |

`p2logit` | Proportions to logit transformed proportions |

`p2asin` | Proportions to arcsine transformed proportions |

`VE2logVR` | Vaccine efficacy / effectiveness to log vaccine ratio |

Note, no function for the Freeman-Tukey arcsine transformation is provided as this transformation is based on the number of events and sample sizes instead of the effect estimates.

R function `transf`

is a wrapper function for the above and
additional transformations, e.g., the log transformation using
`log`

for odds or risk ratios. Argument `sm`

is mandatory to specify the requested transformation. It is also
possible to specify a different function with arguments `func`

and `args`

.

The following auxiliary functions are available to back transform effect estimates or confidence / prediction interval limits.

Function | Transformation |

`asin2ir` | Freeman-Tukey arcsine transformed rates to rates |

`asin2p` | (Freeman-Tukey) arcsine transformed proportions to proportions |

`logit2p` | Logit transformed proportions to proportions |

`logVR2VE` | Log vaccine ratio to vaccine efficacy / effectiveness |

`z2cor` | Fisher's Z transformed correlations to correlations |

Argument `time`

is mandatory in R function `asin2ir`

.

If argument `n`

is provided in R function `asin2p`

,
Freeman-Tukey arcsine transformed proportions are
back transformed. Otherwise, arcsine transformed proportions are
back transformed.

R function `backtransf`

is a wrapper function for the above
and additional transformations, e.g., the exponential
transformation using `exp`

for log odds or log
risk ratios. Argument `sm`

is mandatory to specify the
requested transformation. For the Freeman-Tukey transformations,
argument `n`

or `time`

is mandatory.

It is also possible to specify a different function with arguments
`func`

and `args`

.

Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de

`meta-sm`

```
logit2p(p2logit(0.5))
```

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