combine.est {survcomp} | R Documentation

## Function to combine estimates

### Description

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

### Usage

    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

    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)

[Package survcomp version 1.36.1 Index]