[R] Multilevel modeling using R

[ronggui]

You can use intervals to get the Confidence intervals of fixed and
random effects.

Best

2009/3/17 WONG, Ka Yau <kayau at ied.edu.hk>:
> 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
>
>        [[alternative HTML version deleted]]
>
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>



-- 
HUANG Ronggui, Wincent
Tel: (00852) 3442 3832
PhD Candidate
Dept of Public and Social Administration
City University of Hong Kong
Home page: http://asrr.r-forge.r-project.org/rghuang.html

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