Cohen's d 在多个因子水平的两个分数之间
Cohen's d between two scores for multiple factor levels
我有 9 个不同的因素水平（等级），有两个不同的分数（分数 1 和分数 2）。
我使用以下代码毫无问题地获得了这两个分数之间的效果大小：
cohens_d(df$score1, df$score2)
我想做的是计算每个因子水平的这两个分数之间的效果大小。以下代码不起作用：
df %>%
group_by(class) %>%
cohens_d(score1, score2)
到目前为止，我已经尝试了 lsr、effsize 和 effectsize 软件包，但其中 none 有效。
编辑 2：这是我得到的错误：
Error in .deal_with_cohens_d_arguments(x, y, data) : object 'score1' not found
我的代码的前两行本应 select 数据并按因子水平分组，但似乎不起作用。
df %>%
group_by(class) %>%
提前致谢。
这里是 dput(head(df, 20)) 的结果：
structure(list(`Filter 1` = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), ID = 301:320,
Grade = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("class1",
"class2", "class3", "class4", "class5",
"class6", "class7", "class8", "class9"), class = "factor"),
Class = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("8/D",
"8/G", "8/A", "8/B", "7/E", "7/G", "6/H", "6/D", "5/G", "5/H",
"5CK", "5AA", "adults", "7/D"), class = "factor"), birthdate = c(2005,
2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005,
2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005), Q1 = c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
0L, 1L, 1L, 1L), Q2 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0), Q3 = c(1, 1, 0, 1, 0, 0, 0, 1,
0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1), Q4 = c(1, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0), Q5 = c(0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0), Q6 = c(1,
0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0),
Q7 = c(1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
0, 1, 0), Q8 = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 1, 0, 0, 0, 0), Q9 = c(0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1,
1, 0, 0, 1, 0, 1, 0, 0, 1), Q10 = c(1, 1, 1, 1, 0, 1, 0,
1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0), Q11 = c(1, 0, 0,
0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1), Q12 = c(1,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0),
Q13 = c(0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0,
0, 1, 1), Q14 = c(1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0,
0, 1, 0, 0, 1, 1, 0), Q15 = c(0, 0, 0, 0, 0, 1, 0, 0, 1,
0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0), Q16 = c(1, 0, 1, 0, 1,
1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1), Q17 = c(1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1),
Q18 = c(0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0,
0, 1, 0), Q19 = c(1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0,
1, 1, 0, 0, 0, 0, 0), Q20 = c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0), Q21 = c(1, 0, 1, 0, 1,
0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0), Q22 = c(0,
0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1),
Q23 = c(1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0), Q24 = c(1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0,
1, 1, 1, 0, 0, 0, 0), Q25 = c(1, 1, 1, 0, 0, 1, 0, 0, 1,
0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1), Q26 = c(0, 0, 0, 0, 1,
0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0), Q27 = c(1,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0),
Q28 = c(1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1,
0, 1, 0), Q29 = c(1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0,
0, 1, 1, 0, 0, 1, 0), Q30 = c(0, 0, 0, 0, 1, 0, 0, 1, 1,
0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0), Q31 = c(0, 0, 0, 0, 1,
1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1), Q32 = c(1,
1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0),
Q33 = c(1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0,
0, 0, 1), Q34 = c(1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0,
1, 1, 0, 0, 0, 0, 1), Q35 = c(1, 1, 0, 1, 0, 1, 0, 1, 1,
0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0), Q36 = c(0, 0, 0, 0, 0,
1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0), Q37 = c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0),
Q38 = c(1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L,
0L, 1L, 1L, 0L, 0L, 1L, 0L), Q39 = c(1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0), Q40 = c(1, 1, 1,
0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1), Q41 = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0),
Q42 = c(1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0,
0, 1, 1), Q43 = c(0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0,
1, 1, 1, 0, 0, 1, 0), Q44 = c(0, 0, 0, 1, 0, 1, 1, 1, 1,
0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0), Q45 = c(1, 1, 1, 0, 0,
1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0), Q46 = c(0,
0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0),
Q47 = c(1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0), Q48 = c(0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0,
0, 1, 0, 0, 0, 0, 1), Q49 = c(0, 1, 0, 1, 0, 0, 0, 1, 1,
1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0), Q50 = c(0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0), totalscore = c(30,
16, 19, 15, 15, 24, 17, 32, 36, 20, 19, 42, 12, 18, 40, 25,
6, 9, 21, 15), transformed = c(-0.489961597251375, -1.6416086159321,
-1.29700091350809, -1.78769329956576, -1.78769329956576,
-1.02498741152925, -1.52396770612663, -0.347537009605224,
0.0378608125108563, -1.19639199386294, -1.29700091350809,
0.72280668820074, -2.01768420296626, -1.40146915348254, 0.471079599763142,
-0.94308469425977, -2.93312341654017, -2.57351548813345,
-1.13020640446587, -1.78769329956576), score2= c(8,
5, 4, 6, 2, 6, 4, 9, 9, 8, 6, 10, 2, 7, 11, 8, 2, 1, 5, 5
), score1= c(8, 5, 4, 3, 4, 9, 5, 10, 11, 5, 5, 13,
2, 4, 12, 5, 3, 2, 6, 4)), row.names = c(NA, -20L), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), groups = structure(list(Grade = structure(1L, .Label = c("class1",
"class2", "class3", "class4", "class5",
"class6", "class7", "class8", "class9"), class = "factor"),
.rows = list(1:20)), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE))
这是一个方法。规则很简单，如果你想在 dplyr 管道中计算某些东西，使用 mutate 或 summarise，不要直接管道到你想使用的函数。
library(dplyr)
library(apa)
df %>%
group_by(Class) %>%
mutate(effect = cohens_d(score1, score2))
如果此函数适用于整个数据框：
cohens_d(df$score1, df$score2)
然后考虑 by 到 运行 它跨因子水平到 return 一个 cohens_d 结果的命名列表，其中列表中的项目数等于因子数级别：
cohens_d_list <- by(df, df$grade, function(sub)
cohens_d(sub$score1, sub$score2)
)
cohens_d_list$class1
cohens_d_list$class2
cohens_d_list$class3
...
我有 9 个不同的因素水平（等级），有两个不同的分数（分数 1 和分数 2）。
我使用以下代码毫无问题地获得了这两个分数之间的效果大小：
cohens_d(df$score1, df$score2)
我想做的是计算每个因子水平的这两个分数之间的效果大小。以下代码不起作用：
df %>%
group_by(class) %>%
cohens_d(score1, score2)
到目前为止，我已经尝试了 lsr、effsize 和 effectsize 软件包，但其中 none 有效。
编辑 2：这是我得到的错误：
Error in .deal_with_cohens_d_arguments(x, y, data) : object 'score1' not found
我的代码的前两行本应 select 数据并按因子水平分组，但似乎不起作用。
df %>%
group_by(class) %>%
提前致谢。
这里是 dput(head(df, 20)) 的结果：
structure(list(`Filter 1` = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), ID = 301:320,
Grade = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("class1",
"class2", "class3", "class4", "class5",
"class6", "class7", "class8", "class9"), class = "factor"),
Class = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("8/D",
"8/G", "8/A", "8/B", "7/E", "7/G", "6/H", "6/D", "5/G", "5/H",
"5CK", "5AA", "adults", "7/D"), class = "factor"), birthdate = c(2005,
2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005,
2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005, 2005), Q1 = c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
0L, 1L, 1L, 1L), Q2 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0), Q3 = c(1, 1, 0, 1, 0, 0, 0, 1,
0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1), Q4 = c(1, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0), Q5 = c(0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0), Q6 = c(1,
0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0),
Q7 = c(1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
0, 1, 0), Q8 = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 1, 0, 0, 0, 0), Q9 = c(0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1,
1, 0, 0, 1, 0, 1, 0, 0, 1), Q10 = c(1, 1, 1, 1, 0, 1, 0,
1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0), Q11 = c(1, 0, 0,
0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1), Q12 = c(1,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0),
Q13 = c(0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0,
0, 1, 1), Q14 = c(1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0,
0, 1, 0, 0, 1, 1, 0), Q15 = c(0, 0, 0, 0, 0, 1, 0, 0, 1,
0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0), Q16 = c(1, 0, 1, 0, 1,
1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1), Q17 = c(1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1),
Q18 = c(0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0,
0, 1, 0), Q19 = c(1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0,
1, 1, 0, 0, 0, 0, 0), Q20 = c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0), Q21 = c(1, 0, 1, 0, 1,
0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0), Q22 = c(0,
0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1),
Q23 = c(1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0), Q24 = c(1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0,
1, 1, 1, 0, 0, 0, 0), Q25 = c(1, 1, 1, 0, 0, 1, 0, 0, 1,
0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1), Q26 = c(0, 0, 0, 0, 1,
0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0), Q27 = c(1,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0),
Q28 = c(1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1,
0, 1, 0), Q29 = c(1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0,
0, 1, 1, 0, 0, 1, 0), Q30 = c(0, 0, 0, 0, 1, 0, 0, 1, 1,
0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0), Q31 = c(0, 0, 0, 0, 1,
1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1), Q32 = c(1,
1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0),
Q33 = c(1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0,
0, 0, 1), Q34 = c(1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0,
1, 1, 0, 0, 0, 0, 1), Q35 = c(1, 1, 0, 1, 0, 1, 0, 1, 1,
0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0), Q36 = c(0, 0, 0, 0, 0,
1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0), Q37 = c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0),
Q38 = c(1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L,
0L, 1L, 1L, 0L, 0L, 1L, 0L), Q39 = c(1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0), Q40 = c(1, 1, 1,
0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1), Q41 = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0),
Q42 = c(1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0,
0, 1, 1), Q43 = c(0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0,
1, 1, 1, 0, 0, 1, 0), Q44 = c(0, 0, 0, 1, 0, 1, 1, 1, 1,
0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0), Q45 = c(1, 1, 1, 0, 0,
1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0), Q46 = c(0,
0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0),
Q47 = c(1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0), Q48 = c(0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0,
0, 1, 0, 0, 0, 0, 1), Q49 = c(0, 1, 0, 1, 0, 0, 0, 1, 1,
1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0), Q50 = c(0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0), totalscore = c(30,
16, 19, 15, 15, 24, 17, 32, 36, 20, 19, 42, 12, 18, 40, 25,
6, 9, 21, 15), transformed = c(-0.489961597251375, -1.6416086159321,
-1.29700091350809, -1.78769329956576, -1.78769329956576,
-1.02498741152925, -1.52396770612663, -0.347537009605224,
0.0378608125108563, -1.19639199386294, -1.29700091350809,
0.72280668820074, -2.01768420296626, -1.40146915348254, 0.471079599763142,
-0.94308469425977, -2.93312341654017, -2.57351548813345,
-1.13020640446587, -1.78769329956576), score2= c(8,
5, 4, 6, 2, 6, 4, 9, 9, 8, 6, 10, 2, 7, 11, 8, 2, 1, 5, 5
), score1= c(8, 5, 4, 3, 4, 9, 5, 10, 11, 5, 5, 13,
2, 4, 12, 5, 3, 2, 6, 4)), row.names = c(NA, -20L), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), groups = structure(list(Grade = structure(1L, .Label = c("class1",
"class2", "class3", "class4", "class5",
"class6", "class7", "class8", "class9"), class = "factor"),
.rows = list(1:20)), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE))
这是一个方法。规则很简单，如果你想在 dplyr 管道中计算某些东西，使用 mutate 或 summarise，不要直接管道到你想使用的函数。
library(dplyr)
library(apa)
df %>%
group_by(Class) %>%
mutate(effect = cohens_d(score1, score2))
如果此函数适用于整个数据框：
cohens_d(df$score1, df$score2)
然后考虑 by 到 运行 它跨因子水平到 return 一个 cohens_d 结果的命名列表，其中列表中的项目数等于因子数级别：
cohens_d_list <- by(df, df$grade, function(sub)
cohens_d(sub$score1, sub$score2)
)
cohens_d_list$class1
cohens_d_list$class2
cohens_d_list$class3
...