Comments on: Comparing Multiple Means in R https://www.datanovia.com/en/courses/comparing-multiple-means-in-r/ Data Mining and Statistics for Decision Support Wed, 23 Dec 2020 02:46:26 +0000 hourly 1 https://wordpress.org/?v=6.8.2 By: Matt Berry https://www.datanovia.com/en/courses/comparing-multiple-means-in-r/#comment-21435 Wed, 23 Dec 2020 02:46:26 +0000 https://www.datanovia.com/en/?post_type=dt_courses&p=10870#comment-21435 Having issues with trying to use ggplot to display emmeans pairwise results. I am wanting to see the contrast between all years not just within the same year.
r script:
library(emmeans) ### estimated marginal means and p values
library(sjstats) ### partial eta squared and cohens f effect size
library(lme4) ### estimated the multi level model (random intercept for participants)
library(lmerTest) ### gives more comprehsive anova output with p values
library(MuMIn) ### R2 for the model
library(tidyverse)
library(ggpubr)
library(rstatix)
library(dplyr)
library(readxl)
library(scales)
library(ggsignif)
library(sjPlot)

#load data for One way linear mixed models, repeated measures ##########################
glm_test <- read_excel("C:/Users/maber/Documents/Clover Valley/CLOVER VALLEY/veg data/LPI/UPL_cover.xlsx")
view(glm_test)
head(glm_test, 3)
#factor data#############tell it you have factors and what they are called##############
glm_test$year <- factor(glm_test$year,
levels = c(1, 2, 3),
labels = c("2018", "2019", "2020"))

glm_test$transect <- factor(glm_test$transect,
levels = c(1, 2,3),
labels = c("Lower Meadow", "Middle Meadow", "Upper Meadow"))

###R knows your factors, the below command brakes down your variables
summary(glm_test)

#run linear model with cover as dependent varible, year as #############################
#independent var. for the plot by stating + (1| plot), This makes it a repeated measures
#we call our linear model lmer1
#set up the model use the following code

lmer2 <- lmer(cover ~ as.factor(year) * as.factor(transect) + (1|plot),
data = glm_test)

#linear model dep variable predicted by the indep variable (year)#####################
#run the model with the following code
anova(lmer2)
summary(aov(cover ~ as.factor(year) * as.factor(transect) + Error (plot),
data = glm_test))

#post Hoc comparisons###################################################
#emmeans(lmer2, list(pairwise ~ year), adjust = "bonferroni")

emmeans(lmer2, list(pairwise ~ year), adjust = "tukey")

# if there was an interaction your code would be this###################

emmeans(lmer2, pairwise ~ year | transect)

tab_model(lmer2)

#Visulize data #########################################################

ggboxplot(glm_test, x = "transect", y = "cover", title = "Total % Cover of Upland Species",
ylab = " % Cover UPL Species",
color = "year", ggtheme = theme_gray(base_size = 14))+
scale_x_discrete(labels = label_wrap_gen(7)) +
stat_compare_means(comparisons = my_comparisons, label.y = c(65, 75, 80))+
stat_compare_means(label.y = 82)

The results I want to plot are:
transect = Upper Meadow:
contrast estimate SE df t.ratio p.value
2018 – 2019 27.500 7.15 38 3.848 0.0013
2018 – 2020 20.000 7.15 38 2.798 0.0214
2019 – 2020 -7.500 7.15 38 -1.049 0.5509

Link to HTML doc. file:///C:/Users/maber/Documents/Clover%20Valley/CLOVER%20VALLEY/veg%20data/one%20way%20linear%20mixed%20model,%20repeated%20Meas/two-way_liner_mixed_model_repeated_measures.html
data:
plot transect year cover
D11_NORTH 1 1 24
D11_SOUTH 1 1 16
R27_NORTH 1 1 18
R27_SOUTH 1 1 8
R28_NORTH 1 1 64
R28_SOUTH 1 1 54
D11_NORTH 1 2 46
D11_SOUTH 1 2 38
R27_NORTH 1 2 2
R27_SOUTH 1 2 0
R28_NORTH 1 2 20
R28_SOUTH 1 2 34
D11_NORTH 1 3 44
D11_SOUTH 1 3 36
R27_NORTH 1 3 0
R27_SOUTH 1 3 0
R28_NORTH 1 3 26
R28_SOUTH 1 3 38
D13_NORTH 2 1 44
D13_SOUTH 2 1 30
D14_NORTH 2 1 0
D14_SOUTH 2 1 6
R25_NORTH 2 1 14
R25_SOUTH 2 1 2
R26_NORTH 2 1 20
R26_SOUTH 2 1 42
D13_NORTH 2 2 6
D13_SOUTH 2 2 0
D14_NORTH 2 2 2
D14_SOUTH 2 2 0
R25_NORTH 2 2 0
R25_SOUTH 2 2 14
R26_NORTH 2 2 0
R26_SOUTH 2 2 0
D13_NORTH 2 3 2
D13_SOUTH 2 3 8
D14_NORTH 2 3 0
D14_SOUTH 2 3 10
R25_NORTH 2 3 16
R25_SOUTH 2 3 0
R26_NORTH 2 3 18
R26_SOUTH 2 3 0
R21_NORTH 3 1 32
R21_SOUTH 3 1 82
R22_NORTH 3 1 52
R22_SOUTH 3 1 46
R23_NORTH 3 1 64
R23_SOUTH 3 1 68
R24_NORTH 3 1 8
R24_SOUTH 3 1 8
R21_NORTH 3 2 10
R21_SOUTH 3 2 16
R22_NORTH 3 2 10
R22_SOUTH 3 2 22
R23_NORTH 3 2 48
R23_SOUTH 3 2 28
R24_NORTH 3 2 4
R24_SOUTH 3 2 2
R21_NORTH 3 3 6
R21_SOUTH 3 3 10
R22_NORTH 3 3 16
R22_SOUTH 3 3 14
R23_NORTH 3 3 54
R23_SOUTH 3 3 82
R24_NORTH 3 3 16
R24_SOUTH 3 3 2

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