[R-meta] [metafor package] Metaanalysis using lmer.

[Marcel Lars Meyert]

Hello everyone, 

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:

Warning message:
In optwrap(optimizer, devfun, getStart(start, rho$lower, rho$pp),  :
  convergence code 1 from bobyqa: bobyqa -- maximum number of function
evaluations exceeded

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)
   Data: dat
REML criterion at convergence: 103.1168
Random effects:
 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
 Residual                   3.100e-01      
Number of obs: 165, groups:  Meta_N, 41; Out_alpha, 31; Pub_type, 5;
Country, 2; Lead_construct, 2
Fixed Effects:
(Intercept)   Out_Breuer  
   -0.45167      0.09203  
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.

Best Wishes
Marcel Meyert
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