使用lrtest()和方差分析()进行似然比检验。

Question

请问您对我下面的问题有什么意见？我是做线性回归的，想用似然比检验来比较我的模型。但是，1. 似然比检验 lrtest()似乎不为我工作。我的意思是，我打了 ?lrtest 并无法在R中得到任何文档。

2. 然后，我转移到ANOVA(model1, model2, test ="LRT")。然而，它给了我一个错误。"Error in UseMethod("anova"):no applicable method for 'anova' applied to an object of class "list "I used a data set of the iris as follows.

   data <- data.frame(B = c("m","m","m","m","m", "m", "f","f","f","f","f"),
              G = c("s","s","s","u","u", "u", "k","k","k","r","r"),
              ZN =c(78,82,34,67,98,56,37,45,27,18,34),
              GFR=c(120,100,90,60,100,110,100,90,95,87,96),
              g1 = c(35, 2, 3, 4, 5, 6, 7, 10, 12, 41, 76), 
              g2 = c(20, 2, 7, 2, 8, 5, 5, 3, 7, 2, 12), 
              g3 = c(5, 0, 4, 5, 2, 4, 8, 9, 20, 1, 11),
              g4 = c(1,3,4,5,7,3,1,5,7,3,10),
              g5 = c(20,23, 27, 35, 12, 10, 17, 24, 21, 15, 16),
              g6 = c(13,13,115,17,14,12,19,6,7,8,4),
              g7 = c(5, 0, 4, 5, 2, 4, 8, 9, 20, 1, 11),
              g8 = c(1,3,4,5,7,3,1,5,7,3,10),
              g9 = c(20,23, 27, 35, 12, 10, 17, 24, 21, 15, 16),
              g10 =c(13,13,115,17,14,12,19,6,7,8,4)); 
   
   zn12 <- lapply(data[,-c(1,2,4)], function(x) lm(GFR ~ x + ZN, data = data))
   zn13 <- lm(GFR ~ ZN, data = data)
   anova(zn12,zn13, test="LRT")
   

任何建议将是有帮助的，谢谢你

Answer 1

你可以用评论中介绍的方法，或者用一个 tidyverse

library(tidyverse)
data %>% 
  gather(EP, value, -B:-GFR) %>% 
  split(.$EP)  %>% 
  map(~anova(lm(GFR ~ ZN, data =.),
             lm(GFR ~ value + ZN, data =.),
             test="LRT"))

当你在找p.value的时候，可以试试

data %>% 
  gather(Fac, value, -B:-GFR) %>% 
  split(.$Fac)  %>% 
  map(~anova(lm(GFR ~ ZN, data =.),
             lm(GFR ~ value + ZN, data =.),
             test="LRT") %>%  
        broom::tidy(.) %>% 
        select(p.value) %>% 
        slice(2)) %>% 
  bind_rows(.id = "Factor")
# A tibble: 10 x 2
   Factor p.value
   <chr>    <dbl>
 1 g1     0.467  
 2 g10    0.797  
 3 g2     0.0323 
 4 g3     0.783  
 5 g4     0.403  
 6 g5     0.00556
 7 g6     0.797  
 8 g7     0.783  
 9 g8     0.403  
10 g9     0.00556