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我想拟合一个混合效应模型，让我能够解释不同地理位置的不相等差异。具体来说，我想预测response为固定效应的函数和X随机geo效应。

以下是数据的样子：

         X      response       geo
1        4      5.521461     other
2        4      5.164786     other
3        4      5.164786     other
4        6      3.401197     other
5        5      4.867534     other
6        4      5.010635     other

geo 列的唯一值：

[1] "other"                                   "Atlanta-Sandy Springs-Marietta, GA"      "Chicago-Naperville-Joliet, IL-IN-WI"     "Dallas-Fort Worth-Arlington, TX"        
[5] "Houston-Sugar Land-Baytown, TX"          "Los Angeles-Long Beach-Santa Ana, CA"    "Miami-Fort Lauderdale-Pompano Beach, FL" "Phoenix-Mesa-Glendale, AZ"

这是我尝试过的模型：

> lme0 <- lme(response ~ factor(predictor) , random = ~1|factor(geo), data = HC_hired)
> summary(lme0)
Linear mixed-effects model fit by REML
 Data: HC_hired 
       AIC     BIC    logLik
  54770.69 54836.3 -27377.34

Random effects:
 Formula: ~1 | factor(geo)
        (Intercept) Residual
StdDev:  0.08689381  0.66802

Fixed effects: response ~ factor(predictor) 
                      Value  Std.Error    DF  t-value p-value
(Intercept)        4.255531 0.04410213 26918 96.49264  0.0000
factor(predictor)2 0.022986 0.03336742 26918  0.68889  0.4909
factor(predictor)3 0.166341 0.03221410 26918  5.16361  0.0000
factor(predictor)4 0.299172 0.03194177 26918  9.36618  0.0000
factor(predictor)5 0.378645 0.03249053 26918 11.65402  0.0000
factor(predictor)6 0.472583 0.03664732 26918 12.89543  0.0000
 Correlation: 
                   (Intr) fct()2 fct()3 fct()4 fct()5
factor(predictor)2 -0.660                            
factor(predictor)3 -0.683  0.903                     
factor(predictor)4 -0.689  0.912  0.945              
factor(predictor)5 -0.679  0.897  0.930  0.940       
factor(predictor)6 -0.603  0.795  0.824  0.832  0.819

Standardized Within-Group Residuals:
       Min         Q1        Med         Q3        Max 
-4.7047458 -0.3424262  0.1883132  0.7045260  2.1949313 

Number of Observations: 26931
Number of Groups: 8

我的问题是输出没有为每个地理级别指定随机效果。执行此操作的正确型号规格是什么？我已经尝试了许多公式的排列，但没有运气。也欢迎对整个过程提出任何意见。提前谢谢了！

回应评论（强制地理因素不会改变输出）：

HC_hired$geo <- as.factor(HC_hired$geo) lme0 <- lme(response ~ factor(predictor) , random = ~1|factor(geo), data = HC_hired) 摘要(lme0)

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