[R-meta] Asking for continuous moderating effects
Thank you for your heads up, Professor Viechtbauer. I will keep that in mind. I have attached the sample excel file and the sample code where the problem is to be reproduced. Could you please take a look at these files? As I have a problem with the result I below, I only included the sample data regarding result I. Please let me know if you need anything else to reproduce. Many thanks.
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 still 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
# Moderator 1
res <- rma(rAB, vAB, mods = ~ M1, data=sample_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=sample_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
========================================================================
From: Viechtbauer, Wolfgang (SP) <wolfgang.viechtbauer at maastrichtuniversity.nl>
Sent: Thursday, September 9, 2021 3:05 AM
To: Kim, Jaewoo <jkim at bauer.uh.edu>; r-sig-meta-analysis at r-project.org <r-sig-meta-analysis at r-project.org>
Subject: RE: [R-meta] Asking for continuous moderating effects
?
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 at r-project.org] On Behalf Of Kim, Jaewoo Sent: Thursday, 09 September, 2021 9:46 To: r-sig-meta-analysis at 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
-------------- next part -------------- A non-text attachment was scrubbed... Name: Moderator - sample data.xlsx Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet Size: 71469 bytes Desc: Moderator - sample data.xlsx URL: <https://stat.ethz.ch/pipermail/r-sig-meta-analysis/attachments/20210909/3cc6e527/attachment-0001.xlsx> -------------- next part -------------- A non-text attachment was scrubbed... Name: sample_moderator.R Type: application/octet-stream Size: 208 bytes Desc: sample_moderator.R URL: <https://stat.ethz.ch/pipermail/r-sig-meta-analysis/attachments/20210909/3cc6e527/attachment-0001.obj>