[R-meta] Rationale for performing a moderator test without heterogeneity
racasuso
r@c@@u@o @end|ng |rom ugr@e@
Sat Mar 5 16:34:28 CET 2022
Dear all,
I am performing a meta-analysis on the effects of muscle disuse on
muscle loss. We choose age, duration of the intervention and initial
muscle strength as a priory moderators. The meta-analysis for muscle
loss is as follows:
Random-Effects Model (k = 30; tau^2 estimator: DL)
logLik deviance AIC BIC AICc
-17.9973 27.8366 39.9946 42.7970 40.4391
tau^2 (estimated amount of total heterogeneity): 0 (SE = 0.0511)
tau (square root of estimated tau^2 value): 0
I^2 (total heterogeneity / total variability): 0.00%
H^2 (total variability / sampling variability): 1.00
Test for Heterogeneity:
Q(df = 29) = 27.8366, p-val = 0.5267
Model Results:
estimate se zval pval ci.lb ci.ub
-0.3986 0.0803 -4.9619 <.0001 -0.5561 -0.2412 ***
My first question is if there is any rationale to further perform the
moderator test. In fact, when I perform it for initial force the test of
moderators is significant. How can I interpret this?
Second, I am a little bit confused on how to interpret the test for
moderators when I perform it for each variable in separate and when all
moderators are analysed together. For instance, when I perform the
moderators test for muscle strength it is significant; however, when
both duration and strength are introduced in the model while the
moderator test is significant, only duration reached a significant
effect.
Thank you very much,
Kind regards
--
Rafael A. Casuso
PhD in Health Sciences. Postdoctoral Researcher.
University of Granada.
Department of Physiology.
Email: racasuso using ugr.es
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