### Abstract

With increased use of multivariate meta-analysis in numerous disciplines, where structural relationships among multiple variables are examined, researchers often encounter a particular challenge due to missing information. The current research concerns missing correlations (rs) in the correlation matrix of m variables (R_{m × m}) and establish more informative and empirical prior distributions for missing rs in R_{m × m}. In particular, the method for deriving mathematically/analytically boundaries for missing rs in relation to other adjacent rs in R_{m × m}, while satisfying conditions for a valid R_{m × m} (i.e., a symmetric and positive semidefinite correlation matrix containing real numbers between −1 and 1) is first discussed. Then, a user-defined R package for constructing the empirical distributions of boundaries for rs in R_{m × m} is demonstrated with an example. Furthermore, the applicability of constructing empirical boundaries for rs in R_{m × m} beyond multivariate meta-analysis is discussed.

Original language | English (US) |
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Article number | e1068 |

Journal | Campbell Systematic Reviews |

Volume | 16 |

Issue number | 1 |

DOIs | |

State | Published - Jan 1 2020 |

### Keywords

- boundary
- meta-analysis
- missing correlation

### ASJC Scopus subject areas

- Social Sciences(all)

## Cite this

*Campbell Systematic Reviews*,

*16*(1), [e1068]. https://doi.org/10.1002/cl2.1068