Weighted least squares meta analysis {crwbmetareg} | R Documentation |
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 mtsagris@uoc.gr.
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
Examples
y <- rnorm(30)
vi <- rexp(30, 3)
wlsmeta(y, vi)