gap (version 1.1-16)

metap: Meta-analysis of p values

Description

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.

Usage

metap(data, N, verbose="Y", prefixp="p", prefixn="n")

Arguments

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"

Value

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

See Also

metareg

Examples

## 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. [[e-mail]]
# # 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)