Mixing
Animated violin/boxplots plots with p-values for paired Wilcoxon tests
I am trying to add p values for paired wilcox test in R. I am using the following code. The code below creates violins (density distributions) of an outcome reading (bicep) for two diets (treatment). These violins are animated over time 1, time 2, time 3. And the top of the graph prints p-values. I would like these p-values to be paired values such that
For Diet 'a' Bicep reading at time 2 is compared to time 1, and bicep reading at time 3 is compared to time 1.
And the same for Diet 'b'. So, there should be two separate p-values printed on top of the violins at time 2 and time 3. Indicating paired tests (Time 2 vs Time 1 and Time 3 vs Time 1) for both Diet 'a' and Diet 'b'.
What should be the correct code for this test? I have tried something here below based on a suggestion I got yesterday, but I ran into an error. I also think the code below just does paired tests for Time 2 vs Time 1, and Time 3 vs Time 2. Which is not what I want.
Thanks for reading.
library(ggplot2)
library(ggpubr)
library(gganimate)
library(tidyverse)
Example Data
structure(list(code = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L), diet = c("a",
"a", "a", "b", "b", "b", "a", "a", "a", "b", "b", "b", "a", "a",
"a", "b", "b", "b", "a", "a", "a", "b", "b", "b"), time = c(1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L), bicep = c(8L, 7L, 7L, 9L, 9L, 9L,
11L, 10L, 9L, 11L, 11L, 12L, 12L, 11L, 10L, 9L, 9L, 9L, 12L,
10L, 8L, 12L, 12L, 12L)), class = "data.frame", row.names = c(NA,
-24L))
Example Code
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(example3$bicep, interaction(example3$diet, example3$time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
This is the error I get
Error in mutate_impl(.data, dots) :
Column `p` must be length 8 (the group size) or one, not 25
In addition: There were 15 warnings (use warnings() to see them)
r ggplot2 dplyr gganimate ggpubr
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
add a comment |
I am trying to add p values for paired wilcox test in R. I am using the following code. The code below creates violins (density distributions) of an outcome reading (bicep) for two diets (treatment). These violins are animated over time 1, time 2, time 3. And the top of the graph prints p-values. I would like these p-values to be paired values such that
For Diet 'a' Bicep reading at time 2 is compared to time 1, and bicep reading at time 3 is compared to time 1.
And the same for Diet 'b'. So, there should be two separate p-values printed on top of the violins at time 2 and time 3. Indicating paired tests (Time 2 vs Time 1 and Time 3 vs Time 1) for both Diet 'a' and Diet 'b'.
What should be the correct code for this test? I have tried something here below based on a suggestion I got yesterday, but I ran into an error. I also think the code below just does paired tests for Time 2 vs Time 1, and Time 3 vs Time 2. Which is not what I want.
Thanks for reading.
library(ggplot2)
library(ggpubr)
library(gganimate)
library(tidyverse)
Example Data
structure(list(code = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L), diet = c("a",
"a", "a", "b", "b", "b", "a", "a", "a", "b", "b", "b", "a", "a",
"a", "b", "b", "b", "a", "a", "a", "b", "b", "b"), time = c(1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L), bicep = c(8L, 7L, 7L, 9L, 9L, 9L,
11L, 10L, 9L, 11L, 11L, 12L, 12L, 11L, 10L, 9L, 9L, 9L, 12L,
10L, 8L, 12L, 12L, 12L)), class = "data.frame", row.names = c(NA,
-24L))
Example Code
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(example3$bicep, interaction(example3$diet, example3$time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
This is the error I get
Error in mutate_impl(.data, dots) :
Column `p` must be length 8 (the group size) or one, not 25
In addition: There were 15 warnings (use warnings() to see them)
r ggplot2 dplyr gganimate ggpubr
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
add a comment |
I am trying to add p values for paired wilcox test in R. I am using the following code. The code below creates violins (density distributions) of an outcome reading (bicep) for two diets (treatment). These violins are animated over time 1, time 2, time 3. And the top of the graph prints p-values. I would like these p-values to be paired values such that
For Diet 'a' Bicep reading at time 2 is compared to time 1, and bicep reading at time 3 is compared to time 1.
And the same for Diet 'b'. So, there should be two separate p-values printed on top of the violins at time 2 and time 3. Indicating paired tests (Time 2 vs Time 1 and Time 3 vs Time 1) for both Diet 'a' and Diet 'b'.
What should be the correct code for this test? I have tried something here below based on a suggestion I got yesterday, but I ran into an error. I also think the code below just does paired tests for Time 2 vs Time 1, and Time 3 vs Time 2. Which is not what I want.
Thanks for reading.
library(ggplot2)
library(ggpubr)
library(gganimate)
library(tidyverse)
Example Data
structure(list(code = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L), diet = c("a",
"a", "a", "b", "b", "b", "a", "a", "a", "b", "b", "b", "a", "a",
"a", "b", "b", "b", "a", "a", "a", "b", "b", "b"), time = c(1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L), bicep = c(8L, 7L, 7L, 9L, 9L, 9L,
11L, 10L, 9L, 11L, 11L, 12L, 12L, 11L, 10L, 9L, 9L, 9L, 12L,
10L, 8L, 12L, 12L, 12L)), class = "data.frame", row.names = c(NA,
-24L))
Example Code
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(example3$bicep, interaction(example3$diet, example3$time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
This is the error I get
Error in mutate_impl(.data, dots) :
Column `p` must be length 8 (the group size) or one, not 25
In addition: There were 15 warnings (use warnings() to see them)
r ggplot2 dplyr gganimate ggpubr
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
I am trying to add p values for paired wilcox test in R. I am using the following code. The code below creates violins (density distributions) of an outcome reading (bicep) for two diets (treatment). These violins are animated over time 1, time 2, time 3. And the top of the graph prints p-values. I would like these p-values to be paired values such that
For Diet 'a' Bicep reading at time 2 is compared to time 1, and bicep reading at time 3 is compared to time 1.
And the same for Diet 'b'. So, there should be two separate p-values printed on top of the violins at time 2 and time 3. Indicating paired tests (Time 2 vs Time 1 and Time 3 vs Time 1) for both Diet 'a' and Diet 'b'.
What should be the correct code for this test? I have tried something here below based on a suggestion I got yesterday, but I ran into an error. I also think the code below just does paired tests for Time 2 vs Time 1, and Time 3 vs Time 2. Which is not what I want.
Thanks for reading.
library(ggplot2)
library(ggpubr)
library(gganimate)
library(tidyverse)
Example Data
structure(list(code = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L), diet = c("a",
"a", "a", "b", "b", "b", "a", "a", "a", "b", "b", "b", "a", "a",
"a", "b", "b", "b", "a", "a", "a", "b", "b", "b"), time = c(1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L), bicep = c(8L, 7L, 7L, 9L, 9L, 9L,
11L, 10L, 9L, 11L, 11L, 12L, 12L, 11L, 10L, 9L, 9L, 9L, 12L,
10L, 8L, 12L, 12L, 12L)), class = "data.frame", row.names = c(NA,
-24L))
Example Code
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(example3$bicep, interaction(example3$diet, example3$time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
This is the error I get
Error in mutate_impl(.data, dots) :
Column `p` must be length 8 (the group size) or one, not 25
In addition: There were 15 warnings (use warnings() to see them)
r ggplot2 dplyr gganimate ggpubr
r ggplot2 dplyr gganimate ggpubr
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
edited Nov 21 '18 at 17:37
DiscoR
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
asked Nov 20 '18 at 17:33
DiscoRDiscoR
1179
1179
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
If I understand you problem right then there is very easy solution. You got this error because of wrong syntax inside mutate. There is no need to call for values with $ when you using mutate and pipes %>%:
This code gives a desired animation with minor warnings:
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
UPDATE
In case of independent p-values you just need to add facet_wrap(), for example. It seems to be the easiest:
example3 %>%
group_by(time) %>%
mutate(p = pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max = max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x = diet, y = bicep, fill = diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x = 1, y = max+.5, label = as.character(round(p,2))),
size = 12) +
facet_wrap(~diet, scales = "free_x") + # add facets
theme(legend.position = "none") +
transition_time(time) +
ease_aes('linear')
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for bothaandb. So I can't see the point
– atsyplenkov
Nov 22 '18 at 19:30
1
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
add a comment |
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1 Answer
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1 Answer
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If I understand you problem right then there is very easy solution. You got this error because of wrong syntax inside mutate. There is no need to call for values with $ when you using mutate and pipes %>%:
This code gives a desired animation with minor warnings:
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
UPDATE
In case of independent p-values you just need to add facet_wrap(), for example. It seems to be the easiest:
example3 %>%
group_by(time) %>%
mutate(p = pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max = max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x = diet, y = bicep, fill = diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x = 1, y = max+.5, label = as.character(round(p,2))),
size = 12) +
facet_wrap(~diet, scales = "free_x") + # add facets
theme(legend.position = "none") +
transition_time(time) +
ease_aes('linear')
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for bothaandb. So I can't see the point
– atsyplenkov
Nov 22 '18 at 19:30
1
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
add a comment |
If I understand you problem right then there is very easy solution. You got this error because of wrong syntax inside mutate. There is no need to call for values with $ when you using mutate and pipes %>%:
This code gives a desired animation with minor warnings:
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
UPDATE
In case of independent p-values you just need to add facet_wrap(), for example. It seems to be the easiest:
example3 %>%
group_by(time) %>%
mutate(p = pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max = max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x = diet, y = bicep, fill = diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x = 1, y = max+.5, label = as.character(round(p,2))),
size = 12) +
facet_wrap(~diet, scales = "free_x") + # add facets
theme(legend.position = "none") +
transition_time(time) +
ease_aes('linear')
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for bothaandb. So I can't see the point
– atsyplenkov
Nov 22 '18 at 19:30
1
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
add a comment |
If I understand you problem right then there is very easy solution. You got this error because of wrong syntax inside mutate. There is no need to call for values with $ when you using mutate and pipes %>%:
This code gives a desired animation with minor warnings:
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
UPDATE
In case of independent p-values you just need to add facet_wrap(), for example. It seems to be the easiest:
example3 %>%
group_by(time) %>%
mutate(p = pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max = max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x = diet, y = bicep, fill = diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x = 1, y = max+.5, label = as.character(round(p,2))),
size = 12) +
facet_wrap(~diet, scales = "free_x") + # add facets
theme(legend.position = "none") +
transition_time(time) +
ease_aes('linear')
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
If I understand you problem right then there is very easy solution. You got this error because of wrong syntax inside mutate. There is no need to call for values with $ when you using mutate and pipes %>%:
This code gives a desired animation with minor warnings:
example3 %>%
group_by(time) %>%
mutate(p=pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max=max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x=diet, y=bicep, fill=diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x=1.5, y = max+.5, label=as.character(round(p,2))),
size=12) +
transition_time(time) +
ease_aes('linear')
UPDATE
In case of independent p-values you just need to add facet_wrap(), for example. It seems to be the easiest:
example3 %>%
group_by(time) %>%
mutate(p = pairwise.wilcox.test(bicep, interaction(diet, time), p.adjust.method = "none")$p.value,
max = max(bicep, na.rm = T)) %>%
ggplot() +
geom_violin(aes(x = diet, y = bicep, fill = diet)) +
geom_text(data = . %>% distinct(p, max, time),
aes(x = 1, y = max+.5, label = as.character(round(p,2))),
size = 12) +
facet_wrap(~diet, scales = "free_x") + # add facets
theme(legend.position = "none") +
transition_time(time) +
ease_aes('linear')
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
edited Nov 22 '18 at 19:28
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
answered Nov 22 '18 at 10:22
atsyplenkovatsyplenkov
160111
160111
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for bothaandb. So I can't see the point
– atsyplenkov
Nov 22 '18 at 19:30
1
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
add a comment |
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for bothaandb. So I can't see the point
– atsyplenkov
Nov 22 '18 at 19:30
1
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Thanks! I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins.
– DiscoR
Nov 22 '18 at 16:20
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
Let me clarify a little more. This works but I am looking for a solution where there would be two individual p-values for paired tests printed on top of the two violins. a) paired tests for diet 'a'; Time 3 vs Time 1, and b) paired test for diet 'b' for Time 3 vs Time 1.
– DiscoR
Nov 22 '18 at 16:27
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for both
a and b. So I can't see the point– atsyplenkov
Nov 22 '18 at 19:30
@DiscoR I've just updated the answer. Take a look. However, the p-value are equal for both
a and b. So I can't see the point– atsyplenkov
Nov 22 '18 at 19:30
1
1
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
Thanks, this somewhat solves the problem. The point for having two separate p values is that I am doing a paired wilcoxon test where means of one group at time 3 are compared to means of the same group at time 1. And the same for the other group. So this should result in two separate paired tests. Test 1: Means of Bicep at Time 1 on Diet A compared to Mean of Bicep at Time 12 on Diet A. Test 2: Means of Bicep at Time 1 on Diet B compared to Mean of Bicep at Time 12 on Diet B.
– DiscoR
Nov 23 '18 at 16:37
add a comment |
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