wlsmeta: Weighted least squares meta analysis

In crwbmetareg: Cluster Robust Wild Bootstrap Meta Regression

Weighted least squares meta analysis

Description

Weighted least squares meta analysis.

Usage

wlsmeta(yi, vi)

Arguments

yi	The observations.
vi	The variances of the observations.

Details

It implements weighted least squares (WLS) meta analysis. See references for this.

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.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

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

colwlsmeta

Examples

y <- rnorm(30)
vi <- rexp(30, 3)
wlsmeta(y, vi)

crwbmetareg documentation built on Oct. 19, 2023, 9:06 a.m.