【问题标题】:appending results together from broom::glance将 broom::glance 的结果附加在一起
【发布时间】:2021-07-29 15:09:51
【问题描述】:

假设我有这些数据:

df <- structure(list(a_bracket = structure(c(9L, 8L, 9L, 
9L, 9L, 9L), .Label = c("0-15", "16-20", "21-60", "61-100", "101-500", 
"501-1000", "1001-3500", "3501-5000", "5001+"), class = "factor"), b_bracket = structure(c(3L, 
2L, 3L, 4L, 1L, 4L), .Label = c("18-25", "26-35", "36-40", "41-45", 
"46-48", "49-70", "71+"), class = "factor"), gender = structure(c(2L, 
2L, 2L, 2L, 1L, 2L), .Label = c("Female", "Male"), class = "factor"), 
    q1 = structure(c(2L, 2L, 4L, 3L, 1L, 4L
    ), .Label = c("I don't\nlike a thing", 
    "I don't\na thing at all", "I like a\nthing", 
    "Ambivalent about\nthe thing"), class = "factor"), q2 = structure(c(3L, 
    2L, 1L, 1L, 4L, 1L), .Label = c("Neither like\nnor dislike", 
    "Somewhat\ndislike", "Somewhat\nlike", "Strongly\ndislike", 
    "Strongly\nlike"), class = "factor"), q3 = structure(c(2L, 
    2L, 2L, 3L, 2L, 1L), .Label = c("Moderately", "Not at\nall", 
    "Quite", "Slightly", "Very"
    ), class = "factor")), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

df

# A tibble: 6 x 6
  a_bracket b_bracket gender q1                            q2                          q3           
  <fct>     <fct>     <fct>  <fct>                         <fct>                       <fct>        
1 5001+     36-40     Male   "I don't\na thing at all"     "Somewhat\nlike"            "Not at\nall"
2 3501-5000 26-35     Male   "I don't\na thing at all"     "Somewhat\ndislike"         "Not at\nall"
3 5001+     36-40     Male   "Ambivalent about\nthe thing" "Neither like\nnor dislike" "Not at\nall"
4 5001+     41-45     Male   "I like a\nthing"             "Neither like\nnor dislike" "Quite"      
5 5001+     18-25     Female "I don't\nlike a thing"       "Strongly\ndislike"         "Not at\nall"
6 5001+     41-45     Male   "Ambivalent about\nthe thing" "Neither like\nnor dislike" "Moderately"

我正在尝试运行一系列模型,提取 r 平方和 AIC,并将它们一起附加到一个新的 df 中,并将因变量的名称作为第三行。

这是我的尝试:

model_stats <- function(data){
  
  mod <- glance(
    lm(as.numeric(data) ~ 
         a_bracket + 
         b_bracket + 
         gender, 
       data = df))

  tibble(
    r_squared = mod %>% select(r.squared),
    AIC = mod %>% select(AIC)
  )
}

map_dfr(
  df %>% 
    select(starts_with("q")), 
    model_stats, 
    .id = "question"
) %>% unnest()

但由于某种原因,我不明白这会为我正在运行的模型数量重复输出 N 次。

有谁知道我在这里做错了什么?

【问题讨论】:

    标签: r broom


    【解决方案1】:

    试试这个 -

    library(tidyverse)
    library(broom)
    
    model_stats <- function(data){
      
      mod <- glance(
        lm(as.numeric(data) ~ 
             a_bracket + 
             b_bracket + 
             gender, 
           data = df))
      
      tibble(
        r_squared = mod %>% pull(r.squared),
        AIC = mod %>% pull(AIC)
      )
    
    df %>%
      select(starts_with('q')) %>%
      map_df(model_stats, .id = 'question')
    
    # question r_squared   AIC
    #  <chr>        <dbl> <dbl>
    #1 q1        6.59e- 1  21.8
    #2 q2        7.5 e- 1  20.4
    #3 q3        2.22e-31  20.4
    

    【讨论】:

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