combine.est: Function to combine estimates
In bhklab/survcomp: Performance Assessment and Comparison for Survival Analysis

Description Usage Arguments Value Author(s) References See Also Examples

The function combines several estimators using meta-analytical formula to compute a meta-estimate.

1	combine.est(x, x.se, hetero = FALSE, na.rm = FALSE)

`x`	vector of estimates
`x.se`	vector of standard errors of the corresponding estimates
`hetero`	`TRUE` is the heterogeneity should be taken into account (random effect model), `FALSE` otherwise (fixed effect model)
`na.rm`	`TRUE` if the missing values should be removed from the data, `FALSE` otherwise

`estimate`	meta-estimate
`se`	standard error of the meta-estimate

Benjamin Haibe-Kains

Cochrane, W. G. (1954) "The combination of estimates from different experiments", Biometrics, 10, pages 101–129.

test.hetero.est

set.seed(12345)
x1 <- rnorm(100, 50, 10) + rnorm(100, 0, 2)
m1 <- mean(x1)
se1 <- sqrt(var(x1))
x2 <- rnorm(100, 75, 15) + rnorm(100, 0, 5)
m2 <- mean(x2)
se2 <- sqrt(var(x2))

#fixed effect model
combine.est(x=c(m1, m2), x.se=c(se1, se2), hetero=FALSE)
#random effect model
combine.est(x=c(m1, m2), x.se=c(se1, se2), hetero=TRUE)