使用 anova_test（） 时出现错误消息 - str2lang（x） 中的错误：<text>：1：8：意外输入 1：cbind（1_

Error message when using anova_test() - Error in str2lang(x) : <text>:1:8: unexpected input 1: cbind(1_

提问人：strangecharm 提问时间：7/12/2023 最后编辑：r2evansstrangecharm 更新时间：7/12/2023 访问量：35

问：

当使用新数据运行以前工作的代码时，我收到以下错误：

res.aov <- anova_test(
  data = c1_l1, dv = value, wid = Month,
  within = c(buffer, TimePeriod),
  effect.size = "ges",
  detailed = TRUE,
)
# Error in str2lang(x) : <text>:1:10: unexpected input
# 1: cbind(100_

显然，这表明数据是问题所在，但我不明白为什么会这样。数据已使用与以前相同的过程重新创建，以相同的方式准备，据我所知，它们采用相同的格式和语法。

数据：

> dput(head(c1_l1))
structure(list(buffer = c(2, 3, 4, 5, 6, 7), date = structure(c(18270, 
18270, 18270, 18270, 18270, 18270), class = "Date"), Year = structure(c(3L, 
3L, 3L, 3L, 3L, 3L), levels = c("2016", "2017", "2020"), class = "factor"), 
    Month = c(1, 1, 1, 1, 1, 1), TimePeriod = structure(c(2L, 
    2L, 2L, 2L, 2L, 2L), levels = c("1", "2"), class = "factor"), 
    variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L), levels = c("lst_c1_l1_lst", 
    "lst_c1_l1_single_lst", "lst_c2_l1_lst", "lst_c2_l1_single_lst", 
    "lst_c2_l2_lst"), class = "factor"), value = c(39.42118494, 
    39.46416636, 39.48439384, 39.49212885, 39.23692955, 39.2688776
    )), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"
))

> str(lst)
'data.frame':   2400 obs. of  7 variables:
 $ buffer    : num  200 200 200 200 200 300 300 300 300 300 ...
 $ date      : Date, format: "2020-01-09" "2020-01-09" "2020-01-09" ...
 $ Year      : Factor w/ 3 levels "2016","2017",..: 3 3 3 3 3 3 3 3 3 3 ...
 $ Month     : num  1 1 1 1 1 1 1 1 1 1 ...
 $ TimePeriod: Factor w/ 2 levels "1","2": 2 2 2 2 2 2 2 2 2 2 ...
 $ variable  : Factor w/ 5 levels "lst_c1_l1_lst",..: 1 2 3 4 5 1 2 3 4 5 ...
 $ value     : num  39.4 39.4 39.7 39.7 39.7 ...

法典：

# Some of the below are not used - subsetted from larger R file
library(ggplot2)
library(ggpubr)
library(tidyverse)
library(rstatix)
library(ez)
library(dplyr)

lst <- read.csv("./Data/By metric/LST/landsat_lsts_long.csv", encoding="UTF-8", check.names = FALSE)
str(lst)

lst$buffer <- as.numeric(lst$buffer)
lst$date <- as.Date(lst$date, format = "%d/%m/%Y")
lst$Year <- as.factor(lst$Year)
lst$Month <- as.numeric(lst$Month)
lst$TimePeriod <- as.factor(lst$TimePeriod)
lst$variable <- as.factor(lst$variable)
#lst$weather_variable <- as.factor(lst$weather_variable)

str(lst)

c1_l1 <- as_tibble(filter(lst, variable == "lst_c1_l1_lst"))

res.aov <- anova_test(
  data = c1_l1, dv = value, wid = Month,
  within = c(buffer, TimePeriod),
  effect.size = "ges",
  detailed = TRUE,
)
get_anova_table(res.aov, correction = "auto")

谁能解释错误或提出解决方案？

编辑

较大的数据示例（2400 行中的 500 行）：

> dput(lst[1:500, ])
structure(list(buffer = c(200, 200, 200, 200, 200, 300, 300, 
300, 300, 300, 400, 400, 400, 400, 400, 500, 500, 500, 500, 500, 
600, 600, 600, 600, 600, 700, 700, 700, 700, 700, 800, 800, 800, 
800, 800, 900, 900, 900, 900, 900, 1000, 1000, 1000, 1000, 1000, 
1100, 1100, 1100, 1100, 1100, 1200, 1200, 1200, 1200, 1200, 1300, 
1300, 1300, 1300, 1300, 1400, 1400, 1400, 1400, 1400, 1500, 1500, 
1500, 1500, 1500, 1600, 1600, 1600, 1600, 1600, 1700, 1700, 1700, 
1700, 1700, 1800, 1800, 1800, 1800, 1800, 1900, 1900, 1900, 1900, 
1900, 2000, 2000, 2000, 2000, 2000, 100, 100, 100, 100, 100, 
200, 200, 200, 200, 200, 300, 300, 300, 300, 300, 400, 400, 400, 
400, 400, 500, 500, 500, 500, 500, 600, 600, 600, 600, 600, 700, 
700, 700, 700, 700, 800, 800, 800, 800, 800, 900, 900, 900, 900, 
900, 1000, 1000, 1000, 1000, 1000, 1100, 1100, 1100, 1100, 1100, 
1200, 1200, 1200, 1200, 1200, 1300, 1300, 1300, 1300, 1300, 1400, 
1400, 1400, 1400, 1400, 1500, 1500, 1500, 1500, 1500, 1600, 1600, 
1600, 1600, 1600, 1700, 1700, 1700, 1700, 1700, 1800, 1800, 1800, 
1800, 1800, 1900, 1900, 1900, 1900, 1900, 2000, 2000, 2000, 2000, 
2000, 100, 100, 100, 100, 100, 200, 200, 200, 200, 200, 300, 
300, 300, 300, 300, 400, 400, 400, 400, 400, 500, 500, 500, 500, 
500, 600, 600, 600, 600, 600, 700, 700, 700, 700, 700, 800, 800, 
800, 800, 800, 900, 900, 900, 900, 900, 1000, 1000, 1000, 1000, 
1000, 1100, 1100, 1100, 1100, 1100, 1200, 1200, 1200, 1200, 1200, 
1300, 1300, 1300, 1300, 1300, 1400, 1400, 1400, 1400, 1400, 1500, 
1500, 1500, 1500, 1500, 1600, 1600, 1600, 1600, 1600, 1700, 1700, 
1700, 1700, 1700, 1800, 1800, 1800, 1800, 1800, 1900, 1900, 1900, 
1900, 1900, 2000, 2000, 2000, 2000, 2000, 100, 100, 100, 100, 
100, 200, 200, 200, 200, 200, 300, 300, 300, 300, 300, 400, 400, 
400, 400, 400, 500, 500, 500, 500, 500, 600, 600, 600, 600, 600, 
700, 700, 700, 700, 700, 800, 800, 800, 800, 800, 900, 900, 900, 
900, 900, 1000, 1000, 1000, 1000, 1000, 1100, 1100, 1100, 1100, 
1100, 1200, 1200, 1200, 1200, 1200, 1300, 1300, 1300, 1300, 1300, 
1400, 1400, 1400, 1400, 1400, 1500, 1500, 1500, 1500, 1500, 1600, 
1600, 1600, 1600, 1600, 1700, 1700, 1700, 1700, 1700, 1800, 1800, 
1800, 1800, 1800, 1900, 1900, 1900, 1900, 1900, 2000, 2000, 2000, 
2000, 2000, 100, 100, 100, 100, 100, 200, 200, 200, 200, 200, 
300, 300, 300, 300, 300, 400, 400, 400, 400, 400, 500, 500, 500, 
500, 500, 600, 600, 600, 600, 600, 700, 700, 700, 700, 700, 800, 
800, 800, 800, 800, 900, 900, 900, 900, 900, 1000, 1000, 1000, 
1000, 1000, 1100, 1100, 1100, 1100, 1100, 1200, 1200, 1200, 1200, 
1200, 1300, 1300, 1300, 1300, 1300, 1400, 1400, 1400, 1400, 1400, 
1500, 1500, 1500, 1500, 1500, 1600, 1600, 1600, 1600, 1600, 1700, 
1700, 1700, 1700, 1700, 1800, 1800, 1800, 1800, 1800, 1900, 1900, 
1900, 1900, 1900, 2000, 2000, 2000, 2000, 2000, 100, 100, 100, 
100, 100), date = structure(c(18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 18270, 
18270, 18270, 18270, 18270, 18270, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 17182, 
17182, 17182, 17182, 17182, 17182, 17182, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 18302, 
18302, 18302, 18302, 18302, 18302, 18302, 18302, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 
18334, 18334, 18334, 18334, 18334, 18334, 18334, 18334, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 
17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230, 17230
), class = "Date"), Year = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("2016", 
"2017", "2020"), class = "factor"), Month = c(1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), TimePeriod = structure(c(2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
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    32.53562016)), row.names = c(NA, 500L), class = "data.frame")
r anova rstatix

评论

0赞 Allan Cameron 7/12/2023
请提供足够的数据，以便我们运行您的代码并重现错误。目前，我们得到Error: Variable Month has only one level. Remove it from the model.
0赞 strangecharm 7/12/2023
还行。最好的方法是什么？我去了 dput（lst[1：500， ]）
0赞 r2evans 7/12/2023
显然（可能由 ）通过组合字符串来创建一个表达式，请参阅 github.com/kassambara/rstatix/blob/...。这在我看来既不合理也不安全。factorial_designanova_testcbind

答：

2赞 r2evans 7/12/2023 #1

BLUF：需要 和 中的因子，并使用这些值来形成名称，因此第一个 in 不得以数字开头。anova_testwid=within=within=

如何找到这个问题：

  1. 在源代码中查找，并看到该包通过字符串连接形成表达式（在 factorial_design 中找到）。当您不控制数据时，这通常是一个坏主意，您在这里的问题就是一个很好的例子。（我建议你根据这个问题提交错误报告。cbind

  2. debugonce(factorial_design)，然后评估您对 的调用。由于 中的字符串形成表达式使用 ，我们将逐步完成，直到定义为止。anova_testfactorial_designwide.dv.name

  3. 看值：

    wide.dv.name
# [1] "100_1, 100_2, 1000_1, 1000_2, 1100_1, 1100_2, 1200_1, 1200_2, 1300_1, 1300_2, 1400_1, 1400_2, 1500_1, 1500_2, 1600_1, 1600_2, 1700_1, 1700_2, 1800_1, 1800_2, 1900_1, 1900_2, 200_1, 200_2, 2000_1, 2000_2, 300_1, 300_2, 400_1, 400_2, 500_1, 500_2, 600_1, 600_2, 700_1, 700_2, 800_1, 800_2, 900_1, 900_2"
lm_formula
# [1] "cbind(100_1, 100_2, 1000_1, 1000_2, 1100_1, 1100_2, 1200_1, 1200_2, 1300_1, 1300_2, 1400_1, 1400_2, 1500_1, 1500_2, 1600_1, 1600_2, 1700_1, 1700_2, 1800_1, 1800_2, 1900_1, 1900_2, 200_1, 200_2, 2000_1, 2000_2, 300_1, 300_2, 400_1, 400_2, 500_1, 500_2, 600_1, 600_2, 700_1, 700_2, 800_1, 800_2, 900_1, 900_2) ~ 1"

好吧，这显然不好，R 不喜欢以数字开头的变量。它们由 形成。wide

查看问题值等，这些值由 和 组成，您的参数为 。阅读 的文档，我们看到100_1bufferMonthwithin=anova_test

  within: (optional) within-subjects factor variables

而我们的（和）不是因素。由于如果（形成的字符串的前导部分）以数字字符以外的字符开头，则不太可能发生此问题，因此我们将重点关注此问题。我们可以尝试形成一个（不改变内容），但我怀疑它是否有效，因为那里似乎没有任何验证代码可以区分数字和因子：bufferTimePeriodbufferfactor

c1_l1$bufferf <- factor(c1_l1$buffer)
res.aov <- anova_test(
  data = c1_l1, dv = value, wid = Month,
  within = c(bufferf, TimePeriod),
  effect.size = "ges",
  detailed = TRUE,
)
# Error in str2lang(x) : <text>:1:10: unexpected input
# 1: cbind(100_

好的，确认。让我们试着用一个字母作为前缀。我将快进进行以下更改：buffer

  • buffer：在字母前面加上一个字母并转换为因子
  • TimePeriod和 ：转换为因子Month
c1_l1$buffer_chr <- factor(paste0("b", c1_l1$buffer))
c1_l1$TimePeriod_fct <- factor(c1_l1$TimePeriod)
c1_l1$Month_fct <- factor(c1_l1$Month)
res.aov <- anova_test(
  data = c1_l1, dv = value, wid = Month_fct,
  within = c(buffer_chr, TimePeriod_fct),
  effect.size = "ges",
  detailed = TRUE,
)
# Error in eigen(SSPE, only.values = TRUE)$values >= sqrt(.Machine$double.eps) : 
#   invalid comparison with complex values

但坦率地说，这是一个完全不同的错误，可以通过更完整的数据或通过分析/探索的其他方面来解决。

评论

0赞 strangecharm 7/12/2023
感谢您对正在发生的事情进行彻底的分析。当我阅读时，我想我可以用字母替换缓冲区数字，但这显然是行不通的。不过，我不明白为什么现在会发生这个错误，而以前没有？我是否应该尝试 RStatix 以外的其他软件包，它可能（应该）使用另一种底层方法？
0赞 strangecharm 7/12/2023
很高兴提交错误报告 - 我会在下周初提交。
1赞 r2evans 7/12/2023
我不知道为什么它以前没有犯错，但现在却犯了。我认为这个错误（）的问题已经解决，祝你好运解决你的下一个问题。:-)cbind(100_
0赞 strangecharm 7/12/2023
替代包似乎是“car”和“ez”，还是基本 R？
0赞 strangecharm 7/12/2023
R对我来说只不过是下一个问题...... :)

上一个：ggpubr 缺少显著性注释

下一个：在 R 中隐藏 NS 显著性和括号，使用 geom_pwc、stat_pvalue_manual 或 stat_compare_means