This is the loop that is generating the error.
Error: ! Can't subset columns with
df_numeric[[column]]
. ✖ Can't convert fromdf_numeric[[column]]
to due to loss of precision.
df_numeric <- df[, sapply(df, is.numeric)]
for (column in names(df_numeric)) {
res.aov <- anova_test(data = df, dv= df_numeric[[column]], wid = `Subject`, within = `Timepoint`, between = `Genotype`)
get_anova_table(res.aov)
}
But when I pull out the code for the anova and specifically input the column from my dataframe it generates the proper anova table results.
res.aov <- anova_test(data = df, dv= `Tregs CD127lo CD25+`, wid = `Subject`, within = `Timepoint`, between = `Genotype`)
get_anova_table(res.aov)
I have tried using df_numeric$column
.
Dataframe
library(rstatix)
dput(df_numeric)
structure(list(`Tregs CD127lo CD25+` = c(2702, 2175, 2651, 1672.8,
3762, 4264, 1975, 3208, 3285, 3457, 3383, 2619.9, 11872, 16101,
13443, 3935, 1894, 2297, 7385, 8901, 9522, 7100, 8789, 9309,
371, 379, 514), `Monocytes % of Live by Size` = c(1.38, 2.66,
4.74, 5.83, 3.9, 5.06, 6.36, 3.45, 2.64, 6.33, 10.7, 9.41, 3.42,
3.46, 2.73, 2.38, 3.12, 4.44, 5.31, 3.59, 4.91, 1.53, 6.54, 4.85,
6.87, 3.66, 5.07), `NK cells` = c(90.62, 153.6, 159.8, 88, 118,
159, 74, 82, 64, 30, 344, 73, 29, 198, 79, 145, 258, 307, 30,
74.4, 0, 47.3, 32, 0, 52.6, 95.3, 51.7)), row.names = c(NA, -27L
), class = c("tbl_df", "tbl", "data.frame"))
> dput(df)
structure(list(Subject = c("ASCVD002", "ASCVD002", "ASCVD002",
"ASCVD003", "ASCVD003", "ASCVD003", "ASCVD004", "ASCVD004", "ASCVD004",
"ASCVD005", "ASCVD005", "ASCVD005", "ASCVD006", "ASCVD006", "ASCVD006",
"ASCVD008", "ASCVD008", "ASCVD008", "ASCVD009", "ASCVD009", "ASCVD009",
"ASCVD010", "ASCVD010", "ASCVD010", "ASCVD011", "ASCVD011", "ASCVD011"
), Timepoint = c("0", "0.25", "0.5", "0", "0.25", "0.5", "0",
"0.25", "0.5", "0", "0.25", "0.5", "0", "0.25", "0.5", "0", "0.25",
"0.5", "0", "0.25", "0.5", "0", "0.25", "0.5", "0", "0.25", "0.5"
), Genotype = c("Heterozygote", "Heterozygote", "Heterozygote",
"Heterozygote", "Heterozygote", "Heterozygote", "Heterozygote",
"Heterozygote", "Heterozygote", "GG", "GG", "GG", "AA", "AA",
"AA", "GG", "GG", "GG", "AA", "AA", "AA", "AA", "AA", "AA", "GG",
"GG", "GG"), `Tregs CD127lo CD25+` = c(2702, 2175, 2651, 1672.8,
3762, 4264, 1975, 3208, 3285, 3457, 3383, 2619.9, 11872, 16101,
13443, 3935, 1894, 2297, 7385, 8901, 9522, 7100, 8789, 9309,
371, 379, 514), `Monocytes % of Live by Size` = c(1.38, 2.66,
4.74, 5.83, 3.9, 5.06, 6.36, 3.45, 2.64, 6.33, 10.7, 9.41, 3.42,
3.46, 2.73, 2.38, 3.12, 4.44, 5.31, 3.59, 4.91, 1.53, 6.54, 4.85,
6.87, 3.66, 5.07), `NK cells` = c(90.62, 153.6, 159.8, 88, 118,
159, 74, 82, 64, 30, 344, 73, 29, 198, 79, 145, 258, 307, 30,
74.4, 0, 47.3, 32, 0, 52.6, 95.3, 51.7)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -27L))
Thank you for providing the dput
and code - you are using the df
dataset, so you don't really need the df_numeric
dataset. To get the names of all your numeric columns, you can use the following code: names(df)[unlist(lapply(df, is.numeric))]
. Also you assigned a vector of values to the command dv
- it should only be the name of the column.
The below should work for you, it did for me:
for (column in names(df)[unlist(lapply(df, is.numeric))]) {
res.aov <- rstatix::anova_test(data = df, dv = column,
wid = `Subject`, within = `Timepoint`, between = `Genotype`)
rstatix::get_anova_table(res.aov)
}
Note that in your loop, you are overwriting res.aov
with each iteration and you are not storing the results from get_anova_table(res.aov)
- I would suggest storing these data in a list:
nnames <- names(df)[unlist(lapply(df, is.numeric))]
res.aov <- list()
aov_tab <- list()
for (column in nnames) {
res.aov[[column]] <- rstatix::anova_test(data = df, dv = column,
wid = `Subject`, within = `Timepoint`, between = `Genotype`)
aov_tab[[column]] <- rstatix::get_anova_table(res.aov[[column]])
}