Column-wise weighted least squares meta analysis | R Documentation |

Column-wise weighted least squares meta analysis.

```
colwlsmeta(yi, vi)
```

`yi` |
A matrix with the observations. |

`vi` |
A matrix with the variances of the observations. |

The weighted least squares (WLS) meta analysis is performed in a column-wise fashion. This function is suitable for simulation studies, where one can perform multiple WLS meta analyses at once. See references for this.

A vector with many elements. The fixed effects mean estimate, the `\bar{v}`

estimate, the `I^2`

, the `H^2`

, the Q test statistic and it's p-value,
the `\tau^2`

estimate and the random effects mean estimate.

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

Stanley T. D. and Doucouliagos H. (2015). Neither fixed nor random: weighted least squares meta-analysis. Statistics in Medicine, 34(13), 2116-2127.

` bic.regs `

```
y <- matrix( rnorm(50* 5), ncol = 5)
vi <- matrix( rexp(50* 5), ncol = 5)
colwlsmeta(y, vi)
wlsmeta(y[, 1], vi[, 1])
```

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