Description Usage Arguments Details Value Warning References See Also Examples

Numerically determines the parameter value *m=m_J* of the SGC(*m*) prior,
such that the Hellinger distance between the marginal posteriors for the heterogeneity
standard deviation *τ* induced by the SGC(*m_J*) and Jeffreys (improper) reference prior
is minimal.

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`df` |
data frame with one column "y" containing the (transformed) effect estimates for the individual studies and one column "sigma" containing the standard errors of these estimates. |

`upper` |
upper bound for parameter |

`digits` |
specifies the desired precision of the parameter value |

`mu.mean` |
mean of the normal prior for the effect mu. |

`mu.sd` |
standard deviation of the normal prior for the effect mu. |

See the Supplementary Material of Ott et al. (2021, Section 2.6) for details.

Parameter value *m=m_J* of the SGC(*m*) prior. Real number > 1.

This function takes several minutes to run if the desired precision
is `digits=2`

and even longer for higher precision.

Ott, M., Plummer, M., Roos, M. Supplementary Material:
How vague is vague? How informative is informative? Reference analysis for
Bayesian meta-analysis. Revised for *Statistics in Medicine*. 2021.

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