R 中的因子水平和建模

Question

以下代碼運行一個非常簡單的lm()並嘗試在一個小數據框中總結結果（因子水平、系數）：

df <- data.frame(star_sign = c("Aries", "Taurus", "Gemini", "Cancer", "Leo", "Virgo", "Libra", "Scorpio", "Sagittarius", "Capricorn", "Aquarius", "Pisces"),
                 y = c(1.1, 1.2, 1.4, 1.3, 1.8, 1.6, 1.4, 1.3, 1.2, 1.1, 1.5, 1.3))

levels(df$star_sign) #alphabetical order

# fit a simple linear model

my_lm <- lm(y ~ 1 + star_sign, data = df)
summary(my_lm) # intercept is based on first level of factor, aquarius

# I want the levels to work properly 1..12 = Aries, Taurus...Pisces so I'm going to redefine the factor levels

df$my_levels <- c("Aries", "Taurus", "Gemini", "Cancer", "Leo", "Virgo", "Libra", "Scorpio", "Sagittarius", "Capricorn", "Aquarius", "Pisces")

df$star_sign <- factor(df$star_sign, levels = df$my_levels)

my_lm <- lm(y ~ 1 + star_sign_, data = df)
summary(my_lm) # intercept is based on first level of factor which is now Aries

# but for my model fit I want the reference level to be Virgo (because reasons)

df$star_sign_2 <- relevel(df$star_sign, ref = "Virgo")

my_lm <- lm(y ~ 1 + star_sign_2, data = df)
summary(my_lm)

df_results <- data.frame(factor_level = names(my_lm$coefficients), coeff = my_lm$coefficients )

# tidy up
rownames(df_results) <- 1:12
df_results$factor_level <- as.factor(gsub("star_sign_2", "", df_results$factor_level))

# change label of "(Intercept)" to "Virgo"
df_results$factor_level <- plyr::revalue(df_results$factor_level, c("(Intercept)" = "Virgo"))

levels(df_results$factor_level) # the levels are alphabetical + Virgo at the front (not same as display order from lm)

因子水平的順序不正確：我想對df_results進行排序，以便星座以與它們最初（白羊座、金牛座...雙魚座）相同的順序出現，如df$my_levels列中所捕獲。 我認為我對操縱因素及其標簽/水平等沒有很好的理解，所以我很難知道如何做到這一點。

這也是一段冗長而笨拙的代碼。 有沒有更簡潔的方法來做這種事情？

謝謝你。

（ps 從數學上講，該模型顯然是微不足道的，但對於這些目的來說沒問題——我只是對如何操縱輸出感興趣）

Answer 1

以下是我將如何使用broom包（和dplyr ）進行模型系數提取：

library(broom)
library(dplyr)
broom::tidy(my_lm) %>%
  mutate(term = sub("star_sign_2", "", term),
         term = ifelse(term == "(Intercept)", "Virgo", term),
         term = factor(term, levels = unique(term)))
# A tibble: 12 x 5
   term        estimate std.error statistic p.value
   <fct>          <dbl>     <dbl>     <dbl>   <dbl>
 1 Virgo          1.6         NaN       NaN     NaN
 2 Aries         -0.500       NaN       NaN     NaN
 3 Taurus        -0.4         NaN       NaN     NaN
 4 Gemini        -0.2         NaN       NaN     NaN
 5 Cancer        -0.300       NaN       NaN     NaN
 6 Leo            0.20        NaN       NaN     NaN
 7 Libra         -0.2         NaN       NaN     NaN
 8 Scorpio       -0.3         NaN       NaN     NaN
 9 Sagittarius   -0.4         NaN       NaN     NaN
10 Capricorn     -0.500       NaN       NaN     NaN
11 Aquarius      -0.1         NaN       NaN     NaN
12 Pisces        -0.300       NaN       NaN     NaN

設置levels = unique(term)是一個很好的技巧，可以將級別按出現的順序排列。

我的另一個建議是在數據框中按您不希望的順序保留水平向量，然后在需要建立順序時參考該向量。 例如，

astro_order = c("Aries", "Taurus", "Gemini", "Cancer", "Leo", "Virgo", "Libra", "Scorpio", "Sagittarius", "Capricorn", "Aquarius", "Pisces")

# messy but effective:
astro_order_virgo1 = factor(astro_order, levels = astro_order) %>% 
  relevel("Virgo") %>%
  levels()

那么你可以用term = factor(term, levels = astro_order_virgo1)替換上面的最后一步。

這種將級別順序分開的方法很好，因為 (a) 如果您對數據框重新排序它不會改變，並且 (b) 如果您的數據框很長並且您重復輸入因子級別，它也能正常工作.

Answer 2

如果我理解你需要做什么，這很簡單。 只需在腳本末尾添加以下代碼即可。 我還鼓勵您深入研究 dplyr 或 tidyverse。 如果您有任何問題，請告訴我 :)

## ADDED: 

#WE CREATE AN ID to maintain order in df_results 
df$id <- 1:nrow(df)


library(dplyr)
#Perform left _ join (you could also do inner or right, you'll get the same result in this case )
df_results = left_join(df_results,df, by=c('factor_level'='star_sign_2'))
df_results = df_results %>% arrange(id)

# select desired columns (optionally) 
df_results = df_results %>% select(factor_level,coeff) 


head(df_results)

 factor_level coeff
1        Aries  -0.5
2       Taurus  -0.4
3       Gemini  -0.2
4       Cancer  -0.3
5          Leo   0.2
6        Virgo   1.6