combine.est: Function to combine estimates

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

Description

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

Usage

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

Arguments

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

Value

estimate

meta-estimate

se

standard error of the meta-estimate

Author(s)

Benjamin Haibe-Kains

References

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

See Also

test.hetero.est

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
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)

Example output

Loading required package: survival
Loading required package: prodlim
$estimate
[1] 62.26545

$se
[1] 8.741475

$estimate
[1] 62.9459

$se
[1] 11.37502

survcomp documentation built on Nov. 8, 2020, 4:54 p.m.