Combine p-values by the sum of logs method

Description

Combine p-values by the sum of logs method, also known as Fisher's method

Usage

sumlog(p)
## S3 method for class 'sumlog'
print(x, ...)

Arguments

Details

The method relies on the fact that

sum -2 log p

is a chi-squared with 2 * k df where k is the number of studies.

The values of p should be such that 0<p<=1 and a warning is given if that is not true. An error is given if possibly as a result of deletions fewer than two studies remain.

The plot method for class ‘metap’ calls schweder on the valid p-values. Inspection of the distribution of p-values is highly recommended as extreme values in opposite directions do not cancel out. See last example. This may not be what you want.

Value

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

Author(s)

Michael Dewey

References

Becker, B J. Combining significance levels. In Cooper, H and Hedges, L V, editors A handbook of research synthesis, chapter 15, pages 215–230. Russell Sage, New York, 1994.

Rosenthal, R. Combining the results of independent studies. Psychological Bulletin, 85:185–193, 1978.

Sutton A J, Abrams, K R, Jones D R, Sheldon T A and Song, F. Methods for meta-analysis in medical research. Wiley, Chichester, 2000.

See Also

See also schweder

Examples

data(teachexpect)
sumlog(teachexpect) # chisq = 69.473, df = 38, p = 0.0014, from Becker
data(beckerp)
sumlog(beckerp) # chisq = 18.533, df = 10, sig
data(rosenthal)
sumlog(rosenthal$p) # chisq = 22.97, df = 10, p = 0.006 one sided
data(cholest)
sumlog(cholest) # chisq = 58.62, df = 68, p = 0.78
data(validity)
sumlog(validity) # chisq = 159.82, df = 40, p = 2.91 * 10^{-16}
sumlog(c(0.0001, 0.0001, 0.9999, 0.9999)) # is significant

Results