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I am currently writing a meta-analysis using a pairwise random effects meta-analysis to compare the complication rates of 5 treatment modalities, with one as the gold standard. I was able to get RR's out of the analysis but was not able to get p-values out of it. How do I get the p-values out of it?

drf <- read.csv("drf zonder moroni.csv", sep = ";", header = TRUE, as.is = TRUE)
##
drf <- drf[, 1:5]
names(drf) <- c("study", "type", "treat", "events", "n")

compl <- subset(drf, type == "Complications")

reop <- subset(drf, type == "Reoperations")

library(netmeta)

p.compl <- pairwise(treat = treat, event = events, n = n,
                    studlab = study, data = compl)

n.compl <- netmeta(p.compl, reference = "PC", comb.random=TRUE)
n.compl

netgraph(n.compl, iterate = TRUE, number = TRUE)

Part of dataset

Study| Event Type| Treatment| Number of Events (n)| N| n/N|
Kumaravel| Complications| EF| 3| 23| 0,1304348|
Franck| Complications| EF| 2| 20| 0,1|
Schonnemann| Complications| EF| 8| 30| 0,2666667|
Aita| Complications| EF| 1| 16| 0,0625|
Hove| Complications| EF| 31| 39| 0,7948718|
Andersen| Complications| EF| 26| 75| 0,3466667|
Krughaug| Complications| EF| 22| 75| 0,2933333|
Moroni| Complications| EF| 0| 20| 0|
Plate| Complications| IMN| 3| 30| 0,1|
Chappuis| Complications| IMN| 4| 16| 0,25|
Gradl| Complications| IMN| 12| 66| 0,1818182|
Schonnemann| Complications| IMN| 6| 31| 0,1935484|
Aita| Complications| IMN| 1| 16| 0,0625|
Dremstrop| Complications| IMN| 17| 44| 0,3863636|
Wong| Complications| PC| 1| 30| 0,0333333|
Kumaravel| Complications| PC| 4| 25| 0,16|

enter image description here

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    $\begingroup$ You might do better to ask this on the recently created r-sig-meta-analysis mailing list. $\endgroup$ – mdewey Jul 10 '17 at 16:21
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P values can be derived by n.compl$pval.random

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