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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