# sumz: Combine p-values using the sum of z (Stouffer's) method In metap: Meta-Analysis of Significance Values

 sumz R Documentation

## Combine p-values using the sum of z (Stouffer's) method

### Description

Combine \mjseqnp-values using the sum z method\loadmathjax

### Usage

sumz(p, weights = NULL, data = NULL, subset = NULL, na.action = na.fail,
log.p = FALSE, log.input = FALSE)
## S3 method for class 'sumz'
print(x, ...)


### Arguments

 p \sigvec weights A vector of weights data Optional data frame containing variables subset Optional vector of logicals to specify a subset of the \mjseqnp-values na.action A function indicating what should happen when data contains NAs log.p \logp log.input \loginput x An object of class ‘sumz’ ... Other arguments to be passed through

### Details

Defined as \mjdeqn\frac\sum_i=1^k w_i z(p_i)\sqrt \sum_i=1^k w_i ^ 2sum (w * z(p)) / sqrt(sum (w * w)) is a \mjseqnz where \mjseqnk is the number of studies and \mjseqnw are the weights \insertCitestouffer49metap. By default the weights are equal. In the absence of effect sizes (in which case a method for combining effect sizes would be more appropriate anyway) best results are believed to be obtained with weights proportional to the square root of the sample sizes \insertCitezaykin11metap

\insertNoCite

becker94metap \insertNoCiterosenthal78metap

\ltlt

two If the omitted \mjseqnp values had supplied weights a further warning is issued.

\plotmethod

### Value

An object of class ‘sumz’ and ‘metap’, a list with entries

 z Transformed sum of \mjseqnz values p Associated \mjseqnp-value validp The input vector with illegal values removed weights The weight vector corresponding to validp

Michael Dewey

### References

\insertAllCited

See also plotp

### Examples

data(dat.metap)
teachexpect <- dat.metap$teachexpect sumz(teachexpect) # z = 2.435, p = 0.0074, from Becker beckerp <- dat.metap$beckerp
sumz(beckerp) # z = 1.53, NS, from Beckerp
rosenthal <- dat.metap$rosenthal sumz(rosenthal$p) # 2.39, p = 0.009
sumz(p, df, rosenthal) # 3.01, p = 0.0013
validity <- dat.metap$validity$p
sumz(validity) # z = 8.191, p = 1.25 * 10^{-16}
all.equal(exp(sumz(validity, log.p = TRUE)$p), sumz(validity)$p)
all.equal(sumz(log(validity), log.input = TRUE)$p, sumz(validity)$p)


metap documentation built on March 18, 2022, 7:31 p.m.