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I am a bit confused about doing the meta analysis with my data. Given z-scores I calculate p values in a way: p.values = 2*pnorm(-abs(z)). Then I would like to apply Fischer/or Stouffer methods to do the meta analysis. Those methods work with one-sided p-values, so I just need to divide my p.values by 2 (p.values/2) and perform combine.test(p.values/2) in R?

In this paper I found following: After combining the P-values, if desired the resulting combined P can be again converted to a two-tailed test by multiplying it by two.

So, after I get the combined p values, i multiply them by two to get back to the two-tailed test.

Would it be a correct procedure?

EDIT:

I found this post, saying: Specifically, if two-sided p-values are being analyzed, the two-sided p-value (${p}_i$/2) is used, or 1-${p}_i$ if left-tailed p-values are used.

but I do not understand what is ${p}_i$ in this case. Is ${p}_i$ a two-sided p-value?

I am a bit confused about doing the meta analysis with my data. Given z-scores I calculate p values in a way: p.values = 2*pnorm(-abs(z)). Then I would like to apply Fischer/or Stouffer methods to do the meta analysis. Those methods work with one-sided p-values, so I just need to divide my p.values by 2 (p.values/2) and perform combine.test(p.values/2) in R?

In this paper I found following: After combining the P-values, if desired the resulting combined P can be again converted to a two-tailed test by multiplying it by two.

So, after I get the combined p values, i multiply them by two to get back to the two-tailed test.

Would it be a correct procedure?

EDIT:

I found this post, saying: Specifically, if two-sided p-values are being analyzed, the two-sided p-value (${p}_i$/2) is used, or 1-${p}_i$ if left-tailed p-values are used.

but I do not understand what is ${p}_i$ in this case. Is ${p}_i$ a two-sided p-value?