将nlme语法翻译为MCMCglmm

时间:2015-10-19 10:58:36

标签: r mixed-models

这是nlme

中的模型
library(nlme)
fit1 <- lme(score ~  - 1 + Machine, random=~1|Worker, data=Machines)

MCMCglmm中相应的模型公式是什么? 是吗:

library(MCMCglmm)
fit2 <- MCMCglmm(score ~  - 1 + Machine, 
                 random= ~us(1):Worker, data=Machines)

fit1输出:

> summary(fit1)
Linear mixed-effects model fit by REML
 Data: Machines 
      AIC      BIC    logLik
 296.8782 306.5373 -143.4391

Random effects:
 Formula: ~1 | Worker
      (Intercept) Residual
StdDev:    5.146552 3.161647

Fixed effects: score ~ -1 + Machine 
            Value Std.Error DF  t-value p-value
MachineA 52.35556  2.229312 46 23.48507       0
MachineB 60.32222  2.229312 46 27.05867       0
MachineC 66.27222  2.229312 46 29.72765       0
 Correlation: 
            MachnA MachnB
   MachineB 0.888        
   MachineC 0.888  0.888 

Standardized Within-Group Residuals:
       Min         Q1        Med         Q3        Max 
-2.7248806 -0.5232891  0.1327564  0.6513056  1.7559058 

Number of Observations: 54
Number of Groups: 6 

fit2的输出

> summary(fit2)

 Iterations = 3001:12991
 Thinning interval  = 10
 Sample size  = 1000 

 DIC: 287.5152 

 G-structure:  ~us(1):Worker

                               post.mean l-95% CI u-95% CI eff.samp
(Intercept):(Intercept).Worker     42.29     4.97    120.4     1000

 R-structure:  ~units

      post.mean l-95% CI u-95% CI eff.samp
units     10.51    6.398    15.21     1000

 Location effects: score ~ -1 + Machine 

         post.mean l-95% CI u-95% CI eff.samp  pMCMC    
MachineA     52.36    46.77    57.66     1000 <0.001 ***
MachineB     60.32    55.04    66.34     1000 <0.001 ***
MachineC     66.38    60.61    71.85     1000 <0.001 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

0 个答案:

没有答案