[R-meta] [metafor package] Metaanalysis using lmer.
Marcel Lars Meyert
@tu115300 @ending from m@il@uni-kiel@de
Mon Jul 2 13:19:35 CEST 2018
Thank you so much for accepting me to this newsletter.
As I am fairly new to metaanalysis and especially metaanalysis with R, I
have a question concering the usage of the lmer-command.
The Multilevelanalysis consists of first and second level variables.
The first level variable here is: Diff_comp and the second level
variables: Lead_construct, Out_alpha, Meta_N, Pub_type, Country.
I want to use the lmer-command as following:
Test_analysis = lmer(yi ~ Diff_comp + (Diff_comp | Lead_construct) +
(Diff_comp | Out_alpha) + (Diff_comp | Meta_N) + (Diff_comp | Pub_type)
+ (Diff_comp | Country), data = dat)
As a result I get following message:
In optwrap(optimizer, devfun, getStart(start, rho$lower, rho$pp), :
convergence code 1 from bobyqa: bobyqa -- maximum number of function
Additionally, if I print it, I get the following result:
Linear mixed model fit by REML ['lmerMod']
Formula: yi ~ Out_Breuer + (Out_Breuer | Lead_construct) + (Out_Breuer |
Out_alpha) + (Out_Breuer | Meta_N) + (Out_Breuer | Pub_type) +
(Out_Breuer | Country)
REML criterion at convergence: 103.1168
Groups Name Std.Dev. Corr
Meta_N (Intercept) 0.000e+00
Out_Breuer 6.178e-07 NaN
Out_alpha (Intercept) 2.694e-03
Out_Breuer 2.507e-02 -0.97
Pub_type (Intercept) 3.535e-01
Out_Breuer 9.909e-02 -1.00
Country (Intercept) 2.835e-07
Out_Breuer 1.066e-07 -1.00
Lead_construct (Intercept) 2.586e-01
Out_Breuer 6.867e-02 -1.00
Number of obs: 165, groups: Meta_N, 41; Out_alpha, 31; Pub_type, 5;
Country, 2; Lead_construct, 2
convergence code 1; 0 optimizer warnings; 0 lme4 warnings
My question: Why is the correlation almost always -1.00 ?. Did I use the
command right ?. As I already wrote, I am fairly new to all this and
just want to check, whether I am on the right path, before I present
false results. If any more information is needed, please tell me and I
will respond as soon as possible.
Thank you so much in Advance.
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