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The group appears to have 3 levels based on:
multi.two.group.unpaired.meandiff[[1]]$Group <- factor(multi.two.group.unpaired.meandiff[[1]]$Group, levels = unique(multi.two.group.unpaired.meandiff[[1]]$Group), ordered=FALSE)
The text was updated successfully, but these errors were encountered:
From the earliest stages of designing dabestr, we decided not to allow plotting of the same group twice—both an aesthetic decision and a statistical one: we don't want viewers (and the plotters themselves) to unintentionally perceive the two instances of ASDMLV, for instance in this case.
The UI/UX, however, can be improved: when loading the data into dabestr, and when calling the mean_diff function. (In fact, the effect size functions do allow computation of the effect sizes!!)
On a broader and related topic: there have been several requests (here, here, and here) to perform ANOVA in DABEST: comparing all groups to all other groups. What we consider best practice is to use delta-delta plots. These are still being developed, unfortunately.
You can use estimationstats.com to produce the plot you desire as well, but the second appearance of a repeated group will be colored differently (and given an additional prefix): you can fix this in any vector graphics software.
Error in
levels<-
(*tmp*
, value = as.character(levels)) :factor level [4] is duplicated
Dataframe:
Z-Score_Alpha_Right_Temporal_GroupbyMeasurement.xlsx
Code:
Z_Score_Alpha_Right_Temporal <- read_excel("(https://github.com/ACCLAB/dabestr/files/5042212/Z-Score_Alpha_Right_Temporal_GroupbyMeasurement.xlsx")
multi.two.group.unpaired <-
Z_Score_Alpha_Right_Temporal %>%
dabest(Group, Measurement,
idx = list(c("ASDV", "TD"),
c("ASDMLV", "TD"),
c("ASDMLV", "ASDV")),
paired = FALSE)
multi.two.group.unpaired.meandiff <- mean_diff(multi.two.group.unpaired)
plot(multi.two.group.unpaired.meandiff, color.column = Group)
The group appears to have 3 levels based on:
multi.two.group.unpaired.meandiff[[1]]$Group <- factor(multi.two.group.unpaired.meandiff[[1]]$Group, levels = unique(multi.two.group.unpaired.meandiff[[1]]$Group), ordered=FALSE)
The text was updated successfully, but these errors were encountered: