Dear All,
 
         I use R to conduct multilevel modeling. However, I have a problem about the interpretation of random effect. Unlike the variables in fixed effects, the variables in random effects have not shown the p-value, so I don't know whether they are significant or not? I want to obtain this figure to make the decision.  Thanks a lot! 
 
Below is the syntax and output of my program: 
 
library(nlme)
dataset <- read.csv("d:/dataset.csv")
lme11 <- lme(Overall~1, random=~1|School, method="ML", data=dataset)
summary(lme11)
 
Linear mixed-effects model fit by maximum likelihood
Data: dataset
       AIC      BIC   logLik
  12637.06 12656.27 -6315.53
 
Random effects:
 Formula: ~1 | School
                (Intercept)  Residual
StdDev:   0.2912031 0.9894488        (<-- No p-value)
 
Fixed effects: Overall ~ 1 
                      Value      Std.Error      DF     t-value     p-value
(Intercept) 0.7755495 0.06758038 4444 11.47596       0            (<-- Have p-value)
 
Standardized Within-Group Residuals:
          Min                  Q1                Med                Q3                  Max 
-3.797466473 -0.661750231 -0.007874993  0.652625939  3.549169733 
 
Number of Observations: 4464
Number of Groups: 20 
 
 
Best Regards,
Tommy
Research Assistant of HKIEd

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