[R-meta] Mismatch between P-value and 95% CI in rma()

[Adelina Artenie]

Hi everyone,

I am running a meta-regression analysis for which the outcome is a rate and several continuous moderator variables. I use rma() in metafor to estimate the incidence rate ratio (IRR) associated with a 1-unit increase in the moderator.

If I specify test = "z", my understanding is that both the P-value and the 95%CI are estimated using the Wald test (so results should align). However, I see a small mismatch between the P-value and the 95%CI: the upper bound of the 95% CI is 1.00 (eg: IRR=0.97; 95%CI: 0.94 � 1.00), yet the P-value can be anywhere from P= 0.07 to P= 0.1, depending on the moderator. These P-values seem too high � I would expect them to be closer to 0.05.

I wonder if I am making a mistake in my code or interpretation, or alternatively, if a mismatch like this could occur (though I�ve never encountered it before..) I wonder also if this can have anything to do with the log transformation.

I rely on 95%CI when interpreting my results but I like to also present the P-value, and so I�d like to understand what is happening.

Many thanks for your help.
Best,
Adelina Artenie

**
Code:
My_rma <- rma(measure = "IRLN",
                        xi = cases,
                        ti = prs_yrs_100,
                        add = 0.5,
                        to = "only0",
                        data = Incidence_dat,
                        method = "DL",
                        test = "z",
                        slab = author,
                        mods = ~ moderator )
summary(My_rma)
round(exp(coef(summary(My_rma))[-1,c("estimate", "ci.lb", "ci.ub")]), 2)



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