blme optimizer warnings

Hi everyone,
I am fitting a cross-classified model with blme, but getting 1 optimizer
warning. The code and output are shown below. Any suggestions regarding
fixing the estimation issue? Thanks!

meta.example <- blmer(g~0+(1|Study)+(1|Subscale)+

1|Outcome:Study:Subscale),
+                       data=meta, weights = Variance,
+                       resid.prior = point(1),
+                       control = lmerControl(optimizer="bobyqa"))

meta.example

Cov prior  : Outcome:Study:Subscale ~ wishart(df = 3.5, scale = Inf,
posterior.scale = cov, common.scale = TRUE)
            : Study ~ wishart(df = 3.5, scale = Inf, posterior.scale = cov,
common.scale = TRUE)
            : Subscale ~ wishart(df = 3.5, scale = Inf, posterior.scale =
cov, common.scale = TRUE)
Resid prior: point(value = 1)
Prior dev  : NaN

Linear mixed model fit by maximum likelihood  ['blmerMod']
Formula: g ~ 0 + (1 | Study) + (1 | Subscale) + (1 | Outcome:Study:Subscale)
    Data: meta
Weights: Variance
      AIC      BIC   logLik deviance df.resid
      Inf      Inf     -Inf      Inf       64
Random effects:
  Groups                 Name        Std.Dev.
  Outcome:Study:Subscale (Intercept) 1
  Study                  (Intercept) 1
  Subscale               (Intercept) 1
  Residual                           1
Number of obs: 68, groups:  Outcome:Study:Subscale, 68; Study, 57;
Subscale, 7
No fixed effect coefficients
convergence code 0; 1 optimizer warnings; 0 lme4 warnings




Best,
Sijia

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