crwbmetareg (version 1.0)

Column-wise weighted least squares meta analysis: Column-wise weighted least squares meta analysis

Description

Column-wise weighted least squares meta analysis.

Usage

colwlsmeta(yi, vi)

Value

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.

Arguments

yi

A matrix with the observations.

vi

A matrix with the variances of the observations.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

Details

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.

References

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

Stanley, T. D. and Doucouliagos, H. (2017). Neither fixed nor random: Weighted least squares meta-regression. Research synthesis methods, 8(1): 19--42.

See Also

wlsmeta

Examples

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