[R-meta] Forest Plot with Broken X-axis

[Viechtbauer, Wolfgang (NP)]

Dear Elmira,

Thanks for the reproducible example.

Why not just restrict the x-axis to:

forest(m.gen, xlim=c(-4,4))

This aside, even without knowing further details, I would highly question the results from that one study. For SMDs, a value of 22.66 is just not very plausible. A common issue is that SEs are reported / extracted as SDs, in which case the SMD value will be much larger than it should be.

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>Behalf Of Elmira Agah via R-sig-meta-analysis
>Sent: Tuesday, 25 April, 2023 11:37
>To: R. Special Interest Group for Meta-Analysis
>Cc: Elmira Agah
>Subject: [R-meta] Forest Plot with Broken X-axis
>
>Dear All,
>
>I recently conducted a meta-analysis with R. I just have a problem with the
>forest plot. One study has a large CI, ranging from 19.51 and 25.8, and all the
>other CIs are within the range of 0-4. I want a broken X-axis in my forest plot
>in R like this: -4 -2 0 2 4 // 19 26. I am looking for something like the
>"scale_x_break" function in ggplot2. Although I tried different codes using meta
>and metafor packages, I was unable to achieve the desired result. I would be so
>grateful if you could help me with this matter.
>
>Best regards,
>Elmira
>
>My meta-analysis codes:
>
>library(meta)
>
>dat <- data.frame(
> study = paste0("Study ", 1:28),
> TE = c(1.8984493, 1.9640685, 3.385263, 1.5659699, 1.5652673, 2.0562171,
>0.90219091, 1.0524363, 1.6363198, 2.5232341, 1.4043242, 22.657853, 0.87843556,
>1.3282301, 1.4646563, 2.1925217, 1.2424619, 1.5610836, 0.95507323, 2.3782448,
>2.091292, 1.3451607, 1.2803401, 1.2762723, 2.2864191, 1.5650263, 1.322427,
>1.1478108),
> seTE = c(0.39444893, 0.23328417, 0.29290805, 0.31463743, 0.27502685, 0.30539049,
>0.19348406, 0.19364049, 0.18319501, 0.27044267, 0.2233634, 1.6045138, 0.22649919,
>0.2278701, 0.18908331, 0.33892975, 0.2025052, 0.21445296, 0.3667024, 0.21882009,
>0.36644467, 0.35341581, 0.24426106, 0.27919891, 0.44557554, 0.26745864,
>0.29847459, 0.25620054),
> ci.lb = c(1.1253436, 1.5068399, 2.8111738, 0.94929185, 1.0262246, 1.4576628,
>0.52296911, 0.67290787, 1.2772642, 1.9931762, 0.96653999, 19.513064, 0.4345053,
>0.88161292, 1.0940598, 1.5282316, 0.845559, 1.1407635, 0.23634973, 1.9493653,
>1.3730736, 0.65247847, 0.80159719, 0.72905251, 1.413107, 1.040817, 0.73742752,
>0.64566693),
> ci.ub = c(2.671555, 2.4212971, 3.9593523, 2.1826479, 2.10431, 2.6547715,
>1.2814127, 1.4319646, 1.9953755, 3.053292, 1.8421084, 25.802642, 1.3223658,
>1.7748473, 1.8352528, 2.8568118, 1.6393648, 1.9814037, 1.6737967, 2.8071243,
>2.8095103, 2.037843, 1.759083, 1.8234921, 3.1597311, 2.0892356, 1.9074264,
>1.6499546))
>
>m.gen <- metagen(TE = TE,
> seTE = seTE,
> studlab = study,
> data = dat,
> sm = "SMD",
> comb.fixed = FALSE,
> comb.random = TRUE,
> method.tau = "DL",
>)