[R-meta] Is it normal for Rho (=ICC) to be 1.000 in rma.mv()?
Simon Harmel
@|m@h@rme| @end|ng |rom gm@||@com
Mon May 3 01:26:15 CEST 2021
Dear All,
I have fit the model below. However, rho (= ICC) is estimated to be
"1.0000". Does this mean there is extreme variability between true effects
within each time point? (Or extreme dependence between true effects within
each time point?)
Should I try to find time-related moderators that can potentially explain
some of this variability in the true effects? How low an rho (=ICC) is
reasonably acceptable?
ps: if we set `struct= c("UN","UN")`, we get the following (is this
normal?):
rho.1 rho.2 rho.3 rho.4 1 2 3 4
1 1 1.0000 1.0000 0.5000 - no no no
2 1.0000 1 1.0000 0.5000 31 - no no
3 1.0000 1.0000 1 0.5000 3 3 - no
4 0.5000 0.5000 0.5000 1 1 1 1 -
#-------- My current model:
rma.mv(yi ~ 0 + time + x1 + x2, V = V, struct= c("AR","UN"),
random = list(~time|study, ~1|esid),
data = data)
OUTPUT:
Variance Components:
estim sqrt nlvls fixed factor
sigma^2 0.2117 0.4601 255 no esid
outer factor: study (nlvls = 49)
inner factor: time (nlvls = 4)
estim sqrt fixed
tau^2 0.2679 0.5176 no
rho 1.0000 no <<<--------- Isn't this odd?
Test for Residual Heterogeneity:
QE(df = 249) = 1432.5141, p-val < .0001
Test of Moderators (coefficients 1:6):
QM(df = 6) = 46.1983, p-val < .0001
Model Results:
estimate se zval pval ci.lb ci.ub
time1 0.5928 0.1221 4.8561 <.0001 0.3535 0.8320 ***
time2 0.5671 0.1346 4.2119 <.0001 0.3032 0.8310 ***
time3 0.6288 0.2328 2.7013 0.0069 0.1726 1.0850 **
time4 1.4178 0.4640 3.0556 0.0022 0.5084 2.3272 **
x1 -0.0114 0.0068 -1.6810 0.0928 -0.0248 0.0019 .
x2 0.0133 0.0207 0.6433 0.5200 -0.0272 0.0538
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