library(dplyr)
library(ggplot2)
library(medflex)
library(extrafont)
library(treeio)
library(ggtree)
# data ##################################
# Data source: UPBdata
# individuals who divorced between March 2008 and March 2009
# in four major courts in Flanders
# 385 individuals related to romantic relationship and breakup characteristics
# initiator: of the divorce
# att: anxious attachment level
# negaff: experienced negative affectivity
# attbin: anxious attachment level:
# 1 = higher than sample mean, 0 = lower than sample mean
# attcat: multicategorical anxious attachment level:
# L = low, M = intermediate, H = high
# UPB: displayed unwanted pursuit behavior(s) towards the ex-partner
# load data & selection ---------------------
data(UPBdata, package = "medflex")
head(UPBdata)
str(UPBdata)
UPBdata$UPB = as.factor(ifelse(UPBdata$UPB <= 0.4, "Low", "High"))
my_UPB<-UPBdata%>%dplyr::select(-2,-3)
# transform data set into hclust ############################
hc <- hclust(dist(my_UPB), method = "average")
# transform hclust into Phylo ############################
my_hc<-as.phylo(hc)
# manipluation ##################################
groupInfo <- split(my_hc$tip.label,
gsub("_\\w+", "", my_hc$tip.label))
my_hc2 <- groupOTU(my_hc, groupInfo)
# checking for edges ###################################
edge=data.frame(my_hc2$edge, edge_num=1:nrow(my_hc2$edge))
colnames(edge)=c("parent", "node", "edge_num")
# plotting #######################################
main_plot<-ggtree(my_hc2, aes(color=group), layout='circular',ladderize=F) +
geom_tiplab(size=1, aes(angle=angle)) +
geom_point2(aes(subset=(node==1)), shape=21, size=5, fill='green')+
ggtitle("Unwanted pursuit behavior: \nTree related to romantic relationship and breakup characteristics \non 385 individuals who divorced between March 2008 and March 2009")+
#geom_text(label="")+
#geom_text(data = labels, aes(x, y, label = edu), size = 5)+
labs(subtitle="Strategies for the Estimation of Natural Direct and Indirect Effects of bad relationships",
caption="Multivariate Behavioral Research, Viz Federica Gazzelloni Datasource: R Package medflex Tree Day 16")+
theme_void() +
annotate("text", x = 0, y = 1.018,
label = "Correlated Risk factors",
size = 8,
fontface = "bold",
family = "Courier New")+
theme(legend.position = "none",
plot.title = element_text(family="Andale Mono",color="darkred",size=12),
plot.subtitle = element_text(family="Andale Mono",size=9,color="darkolivegreen"),
plot.caption = element_text(family="Andale Mono",size=8,face="bold"),
axis.text.x = element_text(family="Andale Mono",size=8),
plot.background = element_rect(color = "lightgoldenrod",size=44))
# saving ######################################
ragg::agg_png(here::here("day16_tree", "Tree_day16.png"),
res = 320, width = 14, height = 8, units = "in")
main_plot
dev.off()Load libraries