Meta-analysis of p values
This function is the method of meta-analysis used in the Genetic Investigation of ANThropometric Traits (GIANT) consortium, which is based on normal approximation of p values and weighted by sample sizes from individual studies.
metap(data, N, verbose="Y", prefixp="p", prefixn="n")
data |
data frame |
N |
Number of studies |
verbose |
Control of detailed output |
prefixp |
Prefix of p value, with default value "p" |
prefixn |
Preifx of sample size, with default value "n" |
x2 |
Fisher's chi-squared statistics |
p |
P values from Fisher's method according to chi-squared distribution with 2*N degree(s) of freedom |
z |
Combined z value |
p1 |
One-sided p value |
p2 |
Two-sided p value |
Jing Hua Zhao
## Not run:
s <- data.frame(p1=0.1^rep(8:2,each=7,times=1),n1=rep(32000,49),
p2=0.1^rep(8:2,each=1,times=7),n2=rep(8000,49))
cbind(s,metap(s,2))
# Speliotes, Elizabeth K., M.D. [ESPELIOTES@PARTNERS.ORG]
# 22-2-2008 MRC-Epid JHZ
np <- 7
p <- 0.1^((np+1):2)
z <- qnorm(1-p/2)
n <- c(32000,8000)
n1 <- n[1]
s1 <- s2 <- vector("numeric")
for (i in 1:np)
{
a <- z[i]
for (j in 1:np)
{
b <- z[j]
metaz1 <- (sqrt(n1)*a+sqrt(n[1])*b)/sqrt(n1+n[1])
metap1 <- pnorm(-abs(metaz1))
metaz2 <- (sqrt(n1)*a+sqrt(n[2])*b)/sqrt(n1+n[2])
metap2 <- pnorm(-abs(metaz2))
k <- (i-1)*np+j
cat(k,"\t",p[i],"\t",p[j],"\t",metap1,metaz1,"\t",metap2,metaz2,"\n")
s1[k] <- metap1
s2[k] <- metap2
}
}
q <- -log10(sort(p,decreasing=TRUE))
t1 <- matrix(-log10(sort(s1,decreasing=TRUE)),np,np)
t2 <- matrix(-log10(sort(s2,decreasing=TRUE)),np,np)
par(mfrow=c(1,2),bg="white",mar=c(4.2,3.8,0.2,0.2))
persp(q,q,t1)
persp(q,q,t2)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.