metap-package {metap}

Meta-Analysis of Significance Values

Description

The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Lancaster, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and routines for graphical display.

Details

Index of help topics:

albatros                Albatros plot
allmetap                Carry out all or some of the methods in the
                        package
dat.metap               Example data
invchisq                Combine p values using the inverse chi squared
                        method
invt                    Combine p values using the inverse t method
logitp                  Combine p values using the logit method
meanp                   Combine p values by the mean p method
meanz                   Combine p values using the mean z method
metap-package           Meta-Analysis of Significance Values
plotp                   Q-Q plot of p-values
schweder                Schweder and Spjotvoll plot
sumlog                  Combine p-values by the sum of logs (Fisher's)
                        method
sump                    Combine p-values using the sum of p
                        (Edgington's) method
sumz                    Combine p-values using the sum of z
                        (Stouffer's) method
truncated               Truncated product methods
two2one                 Convert two-sided p-values to one-sided
votep                   Combine p-values by the vote counting method
wilkinsonp              Combine p-values using Wilkinson's method

Further information is available in the following vignettes:

compare	Comparison of methods in the metap package (source)
metap	Introduction to the metap package (source)
plotmetap	Plotting in the metap package (source)

Provides a number of ways in which significance levels may be combined in a meta-analysis and includes most ot the methods in Becker (1994). It includes a number of datasets taken from the literature. It also provides a display and an informal graphical test due to Schweder and Spjotvoll (Schweder and Spjotvoll 1982) and the lowest slope line of Benjamini and Hochberg (Benjamini and Hochberg 2000). The albatros plot of Harrison et al (Harrison et al. 2017) is also provided.

References

Becker BJ (1994). “Combining significance levels.” In Cooper H, Hedges LV (eds.), A handbook of research synthesis, 215–230. Russell Sage, New York.

Benjamini Y, Hochberg Y (2000). “On the adaptive control of the false discovery rate in multiple testing with independent statistics.” Journal of Educational and Behavioral Statistics, 25, 60–83.

Harrison S, Jones HE, Martin RM, Lewis SJ, Higgins JPT (2017). “The albatros plot: A novel graphical tool for presenting the results of diversely reported studies in a systematic review.” Research Synthesis Methods, 8, 281–289.

Schweder T, Spjotvoll E (1982). “Plots of P–values to evaluate many tests simultaneously.” Biometrika, 69, 493–502.

See Also

The issue of meta-analysis of signficance levels is not completely unconnected with the topic of adjustment for multiple comparisons as in for example p.adjust