R 中的单向方差分析有几个问题

Question

我的输出是这样的：

structure(list(Year = 2006:2021, Month_USD = c(1160L, 1240L, 1360L, 1480L, 1320L, 1320L, 375L, 1600L, 2000L, 2000L, 1600L, 2240L, 1900L, 2300L, 2900L, 2300L), Degree = c("High School", "High School", "High School", "High School", "High School", "High School", "High School", "High School", "High School", "BA", "BA", "BA", "BA", "BA", "M.Ed", "M.Ed"), Country = c("USA", "USA", "USA", "USA", "USA", "USA", "DE", "USA", "USA", "USA", "USA", "USA", "PRC", "PRC", "PRC", "HK"), Job = c("Disher", "Prep", "Prep", "Prep", "Prep", "Prep", "Au Pair", "CSA", "Valet", "Valet", "Intake", "CM", "Teacher", "Teacher", "Teacher", "Student"), Median_Household_Income_US = c(4833L, 4961L, 4784L, 4750L, 4626L, 4556L, 4547L, 4706L, 4634L, 4873L, 5025L, 5218L, 5360L, 5725L, NA, NA), US_Home_Price_Index = c(183.24, 173.36, 152.56, 146.69, 140.64, 135.16, 143.88, 159.3, 166.5, 175.17, 184.51, 195.99, 204.9, 212.59, 236.31, NA)), class = "data.frame", row.names = c(NA, -16L))

因此，我对这些数据进行了单向方差分析，但遇到了一些问题。 首先，当我在这里运行关卡 function 时：

data(Earnings_Year)
View(Earnings_Year)
set.seed(1234)
Earnings_Year %>% 
  sample_n_by(Degree,
              size=1)
levels(Earnings_Year$Degree)

无论出于何种原因，上面的代码都不会显示级别，只会吐出“NULL”。 据我所知，级别应该是“BA”、“High School”和“M.Ed”。

我后来遇到的另一个问题是我运行它的时候。 当我运行一个通用的 Shapiro 测试时，似乎没有相同的问题，直到我将它分组：

Earnings_Year %>% 
  group_by(Degree) %>% 
  shapiro_test(Month_USD)

当我运行它时，它会出现以下问题：

Error: Problem with `mutate()` column `data`.
i `data = map(.data$data, .f, ...)`.
x Problem with `mutate()` column `data`.
i `data = map(.data$data, .f, ...)`.
x sample size must be between 3 and 5000
Run `rlang::last_error()` to see where the error occurred.

对出了什么问题的任何见解将不胜感激。 总的来说，最后我得到了一个不错的方差分析箱线图，它似乎表明了我在寻找什么：

Answer 1

正如错误消息所暗示的那样，您的数据中有某些组少于 3 行或多于 5000 行。

我们可以使用count检查每组中的行数。

library(dplyr)
library(rstatix)

df %>% count(Degree)

#       Degree n
#1          BA 5
#2 High School 9
#3        M.Ed 2

您可以删除此类组，代码应该可以正常工作。

df %>%
  group_by(Degree) %>%
  filter(n() > 2) %>%
  shapiro_test(Month_USD)

# Degree      variable  statistic     p
#  <chr>       <chr>         <dbl> <dbl>
#1 BA          Month_USD     0.944 0.695
#2 High School Month_USD     0.887 0.185