test.hetero.test: Function to test the heterogeneity of set of probabilities In survcomp: Performance Assessment and Comparison for Survival Analysis

Description

The function tests whether a set of p-values are heterogeneous.

Usage

 `1` ```test.hetero.test(p, weight, na.rm = FALSE) ```

Arguments

 `p` vector of p-values `weight` vector of weights (e.g. sample size of each study) `na.rm` `TRUE` if the missing values should be removed from the data, `FALSE` otherwise

Details

The p-values should be one-sided and computed from the same null hypothesis.

Value

 `Q` Q statistic `p.value` p-value of the heterogeneity test

Author(s)

Benjamin Haibe-Kains

References

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

Whitlock, M. C. (2005) "Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach", J. Evol. Biol., 18, pages 1368–1373.

`combine.test`

Examples

 ```1 2 3 4 5 6 7``` ```p <- c(0.01, 0.13, 0.07, 0.2) w <- c(100, 50, 200, 30) #with equal weights test.hetero.test(p=p) #with p-values weighted by the sample size of the studies test.hetero.test(p=p, weight=w) ```

Example output

```Loading required package: survival
\$Q
[1] 1.243275

\$p.value
[1] 0.7426449

\$Q
[1] 94.16364

\$p.value
[1] 2.792858e-20
```

survcomp documentation built on Nov. 20, 2017, 2:01 a.m.