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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