combine.test {survcomp} | R Documentation |
The function combines several p-value estimated from the same null hypothesis in different studies involving independent data.
combine.test(p, weight, method = c("fisher", "z.transform", "logit"), hetero = FALSE, na.rm = FALSE)
p |
vector of p-values |
weight |
vector of weights (e.g. sample size of each study) |
method |
fisher for the Fisher's combined probability test, z.transform for the Z-transformed test, logit for the weighted Z-method |
hetero |
TRUE is the heterogeneity should be taken into account, FALSE otherwise |
na.rm |
TRUE if the missing values should be removed from the data, FALSE otherwise |
The p-values must be one-sided and computed from the same null hypothesis.
p-value
Benjamin Haibe-Kains
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.
test.hetero.test
p <- c(0.01, 0.13, 0.07, 0.2) w <- c(100, 50, 200, 30) #with equal weights combine.test(p=p, method="z.transform") #with p-values weighted by the sample size of the studies combine.test(p=p, weight=w, method="z.transform")