[R-meta] Asking for continuous moderating effects

[Viechtbauer, Wolfgang (SP)]

Dear Jaewoo,

Please provide a reproducible example for the case where R^2 is reported as NA%.

Also, please switch of line wrapping in your email client (or whatever is causing the results below to be so mangled up).

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>Behalf Of Kim, Jaewoo
>Sent: Thursday, 09 September, 2021 9:46
>To: r-sig-meta-analysis using r-project.org
>Subject: [R-meta] Asking for continuous moderating effects
>
>Hello,
>
>Hope that this email goes well. I am analyzing continuous moderating effects with
>metafor. When I ran the moderator analysis, I found that R^2 is NA%. Since my
>metafor is an older version, I thought NA appeared in the results. Though I
>updated my metafor (v 3.0-2), the results were the same (please see the result I).
>However, when I ran another moderator analysis with metafor, R^2 appeared 0, not
>NA (please see result II). May I ask why this happens? In this case, can I view NA
>as 0%? Below are the results with R code.
>
>Results I
>
>res <-
>rma(rAB, vAB, mods = ~ M1, data=en_moderator)
>res
>
>Mixed-Effects
>Model (k = 17; tau^2 estimator: REML)
>
>tau^2
>(estimated amount of residual heterogeneity):     0.0069 (SE = 0.0112)
>tau (square
>root of estimated tau^2 value):
>0.0830
>I^2 (residual
>heterogeneity / unaccounted variability): 22.42%
>H^2
>(unaccounted variability / sampling variability):   1.29
>R^2 (amount
>of heterogeneity accounted for):
>NA%
>
>Test for
>Residual Heterogeneity:
>QE(df = 15) =
>16.9198, p-val = 0.3237
>
>Test of
>Moderators (coefficient 2):
>QM(df = 1) =
>9.4482, p-val = 0.0021
>
>Model
>Results:
>
>         estimate      se
>zval    pval    ci.lb
>ci.ub
>intrcpt   -0.5843
>0.2530  -2.3094  0.0209
>-1.0802  -0.0884   *
>M1         0.2672
>0.0869   3.0738  0.0021
>0.0968   0.4375  **
>
>===================================================================
>
>Results II
>
>res <-
>rma(rAE, vAE, mods = ~ M1, data=en_moderator)
>res
>
>Mixed-Effects
>Model (k = 10; tau^2 estimator: REML)
>
>tau^2
>(estimated amount of residual heterogeneity):     0.0291 (SE = 0.0194)
>tau (square
>root of estimated tau^2 value):
>0.1705
>I^2 (residual
>heterogeneity / unaccounted variability): 77.99%
>H^2
>(unaccounted variability / sampling variability):   4.54
>R^2 (amount
>of heterogeneity accounted for):
>0.00%
>
>Test for
>Residual Heterogeneity:
>QE(df = 8) =
>37.9082, p-val < .0001
>
>Test of
>Moderators (coefficient 2):
>QM(df = 1) =
>0.9967, p-val = 0.3181
>
>Model
>Results:
>
>         estimate      se
>zval    pval    ci.lb
>ci.ub
>intrcpt    0.4235
>0.2087   2.0297  0.0424
>0.0146  0.8325  *
>M1        -0.0862
>0.0863  -0.9984  0.3181
>-0.2554  0.0830