方差分析 (rstatix) 中“mutate()”输入“数据”的问题

Question

这真让我抓狂。我正在使用anova_testfrom rstatix，它告诉我，当我的列明显存在时，它们不存在。

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这就是我的数据框的样子：

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ID = c(1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3) \nForm = c("A", "A", "A", "B", "B", "B", "A", "A", "A", "B", "B", "B", "A", "A", "A", "B", "B", "B")\nPen = c("Red", "Blue", "Green", "Red", "Blue", "Green", "Red", "Blue", "Green","Red", "Blue", "Green","Red", "Blue", "Green","Red", "Blue", "Green")\nTime = c(20, 4, 6, 2, 76, 3, 86, 35, 74, 94, 14, 35, 63, 12, 15, 73, 87, 33)\ndf <- data.frame(ID, Form, Pen, Time)\n

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ID、Form 和 Pen 是因子，而 Time 是数字。因此，每个受试者都用红、蓝、绿笔完成表格 A 和 B，我测量了每个受试者完成表格所需的时间。

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这是我故意提出的一个假数据集来问这个问题。实际上，该数据框源自具有更多变量的更大数据集。每个变量都有更多的观察结果（因此，不仅仅是主题 1 和表格 A 和红笔的一个数据点，如本例所示，而是多个），因此我对它们进行了总结以获得平均时间。

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df <- original.df %>% dplyr::select(ID, Form, Pen, Time)\ndf <- df %>% dplyr::group_by(ID, Form, Pen) %>% dplyr::summarise(Time = mean(Time))\ndf <- df %>% convert_as_factor(ID, Form, Pen)\ndf$Time <- as.numeric(df$Time)\n

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我想测试主效应和交互效应，所以我正在做 2 x 3 重复测量方差分析（双向方差分析，因为 Form 和 Pen 是两个自变量）。

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aov <- rstatix::anova_test(data = df, dv = Time, wid = ID, within = c(Form, Pen))\n

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我不断收到此错误：

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Error: Problem with `mutate()` input `data`.\nx Can't subset columns that don't exist.\nx Columns `ID` and `Form` don't exist.\n\xe2\x84\xb9 Input `data` is `map(.data$data, .f, ...)`.\n

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为什么？！任何帮助将不胜感激。我已经花了几个小时寻找解决方案，但我感到非常沮丧。

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Answer 1

感谢您在帖子中添加额外的详细信息 - 根据您提供的内容，您似乎需要在将 df 传递给之前取消分组anova_test()，例如

#install.packages("rstatix")
library(rstatix)
library(tidyverse)

ID = c(1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3) 
Form = c("A", "A", "A", "B", "B", "B", "A", "A", "A", "B", "B", "B", "A", "A", "A", "B", "B", "B")
Pen = c("Red", "Blue", "Green", "Red", "Blue", "Green", "Red", "Blue", "Green","Red", "Blue", "Green","Red", "Blue", "Green","Red", "Blue", "Green")
Time = c(20, 4, 6, 2, 76, 3, 86, 35, 74, 94, 14, 35, 63, 12, 15, 73, 87, 33)
original.df <- data.frame(ID, Form, Pen, Time)

df <- original.df %>%
  dplyr::select(ID, Form, Pen, Time)
df <- df %>%
  dplyr::group_by(ID, Form, Pen) %>%
  dplyr::summarise(Time = mean(Time))
df <- df %>%
  convert_as_factor(ID, Form, Pen)
df$Time <- as.numeric(df$Time)
df <- ungroup(df)

aov <- rstatix::anova_test(data = df, dv = Time, wid = ID, within = c(Form, Pen))

您可以查看数据帧是否使用 进行分组str()，例如str(df)before 和 afterungrouped()向您显示差异。如果进行此更改后仍然出现错误，请告诉我