[R-sig-ME] Advice on Mixed Models

[Rose Rosei]

Dear Advisors

Would you please advise me. I would like to fit my model, but I struggled
to do it


  A= Applicant = 10 persons
  S= Stream ( four levels, 1, 2)
  D= Day   (1,2)
 S1= Session ( 1,2)
 Q = Qestion ( 1-to 8)
 Applicants are crossed in Questions, but Applicants nested in Stream,
  nested in Day, nested in session (S1). All variables are a a random factor

   I want to calculate SD for A, S, D, S1 and Q, and their interaction
.score=dependent variable

 I have used the following codes, but it seems they are wrong.

 lmer(score~ (1|A)+(1|S)+(1+D)+(1|S1)+(1|Q)+(1|A/S)+1|S/D)+(1|D/S1)+(1|S1/Q),
R)

Linear mixed model fit by REML ['lmerMod']
Formula: score ~ (1 | A) + (1 | S) + (1 + D) + (1 | S1) + (1 | Q) + (1 |
    A/S) + (1 | S/D) + (1 | D/S1) + (1 | S1/Q)
   Data: R
REML criterion at convergence: 192.4591
Random effects:
 Groups   Name        Std.Dev.
 Q.S1     (Intercept) 0.000e+00
 A        (Intercept) 2.383e-01
 S.A      (Intercept) 7.692e-01
 A.1      (Intercept) 8.399e-01
 Q        (Intercept) 0.000e+00
 S1.D     (Intercept) 1.386e-08
 D.S      (Intercept) 0.000e+00
 S1       (Intercept) 0.000e+00
 D        (Intercept) 9.498e-01
 S        (Intercept) 0.000e+00
 S1.1     (Intercept) 0.000e+00
 S.1      (Intercept) 0.000e+00
 Residual             6.722e-01
Number of obs: 80, groups:
Q:S1, 16; A, 10; S:A, 10; Q, 8; S1:D, 4; D:S, 4; S1, 2; D, 2; S, 2
Fixed Effects:
(Intercept)            D
    1.61458     -0.07292
convergence code 0; 2 optimizer warnings; 0 lme4 warnings

   Very much appreciated for your help.
looking forward to hearing from you.
   Rose

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