2012-01-28 22 views
7

我可以使用summary(fm1)从nlme摘要中提取固定效果。但挣扎如何得到Random effects:部分。从nlme摘要中提取随机效果

fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject) 
summary(fm1) 
Linear mixed-effects model fit by REML 
Data: Orthodont 
     AIC  BIC logLik 
    454.6367 470.6173 -221.3183 

Random effects: 
Formula: ~age | Subject 
Structure: General positive-definite, Log-Cholesky parametrization 
      StdDev Corr 
(Intercept) 2.3270340 (Intr) 
age   0.2264278 -0.609 
Residual 1.3100397  

Fixed effects: distance ~ age 
       Value Std.Error DF t-value p-value 
(Intercept) 16.761111 0.7752460 80 21.620377  0 
age   0.660185 0.0712533 80 9.265333  0 
Correlation: 
    (Intr) 
age -0.848 

Standardized Within-Group Residuals: 
     Min   Q1   Med   Q3   Max 
-3.223106086 -0.493761144 0.007316631 0.472151121 3.

Number of Observations: 108 
Number of Groups: 27 

任何帮助将不胜感激。谢谢

回答

9

使用ranef(fm1)来提取每个主题。

更新给代码从汇总表提取:

>VarCorr(fm1) 
Subject = pdLogChol(age) 
      Variance StdDev Corr 
(Intercept) 5.41508758 2.3270341 (Intr) 
age   0.05126955 0.2264278 -0.609 
Residual 1.71620400 1.3100397 

> temp <- VarCorr(fm1) 
> temp[,2] 
(Intercept)   age Residual 
"2.3270341" "0.2264278" "1.3100397" 

> temp[1,2] 
[1] "2.3270341" 
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谢谢您的回答。 'ranef'给出了随机效果,但是来自'summary(fm1)'的'Random Effects:'中的StdDev部分。 – MYaseen208 2012-01-28 08:42:49

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不错。我正在跟踪lme对象的print/summary路径,但在'print.modelStruct'处丢失了。 – 2012-01-28 10:29:02

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谢谢,我很欣赏我对答案的反馈,因为它可以帮助我在未来提供更好的答案。 :) – Michelle 2012-01-28 18:19:04