Line Diagrams

Simple simulated data (used in L1)

First, we generate simple data on 20 participants as describe by L1:

“Say you wish to estimate the 5-year risk of death among people entering HIV care. You have a database of people entering HIV care between 2012 and 2020.”

### Generate some data -----
require(dplyr)
set.seed(123)
year0 <- runif(20, min=2012, max = 2020)
t <- runif(20, min=2, max = 15)
dat <- data.frame(year0, t)


dat <- dat %>% mutate(y=ifelse(t+year0>2020 | t>5, 0, 1),
                      t = ifelse(t+year0>2020, 2020-year0, t), 
                      t = ifelse(t>5, 5, t),
                      id = row_number())

dat

##       year0         t y id
## 1  2014.301 5.0000000 0  1
## 2  2018.306 1.6935589 0  2
## 3  2015.272 4.7281846 0  3
## 4  2019.064 0.9358608 0  4
## 5  2019.524 0.4762617 0  5
## 6  2012.364 5.0000000 0  6
## 7  2016.225 3.7751561 0  7
## 8  2019.139 0.8606476 0  8
## 9  2016.411 3.5885199 0  9
## 10 2015.653 3.9124774 1 10
## 11 2019.655 0.3453332 0 11
## 12 2015.627 4.3733268 0 12
## 13 2017.421 2.5794349 0 13
## 14 2016.581 3.4189328 0 14
## 15 2012.823 2.3199779 1 15
## 16 2019.199 0.8014002 0 16
## 17 2013.969 5.0000000 0 17
## 18 2012.336 4.8133032 1 18
## 19 2014.623 5.0000000 0 19
## 20 2019.636 0.3639708 0 20

Produce the line diagram by creating line segments and points in ggplot.

# Calendar time as timescale
library(grid)
library(ggthemr)
ggthemr('solarized')
line <- ggplot() +
  geom_segment(data = dat %>% filter(y==0), aes(x = year0, y = id, xend = year0+t, yend = id),  arrow = arrow(length = unit(0.1, "cm"))) +
  geom_segment(data = dat %>% filter(y==1), aes(x = year0, y = id, xend = year0+t, yend = id)) +
  scale_y_continuous(name = "ID", breaks = c(1, 5, 10, 15, 20), limits = c(0,20))+
  scale_x_continuous(name = "Calendar Time", breaks=c(2012, 2014, 2016, 2018,  2020), limits = c(2012, 2021)) +
  geom_point(data = dat %>% filter(y==1), aes(x = year0+t, y = id), color = "red", size = 0.6) +
  theme(text = element_text(size = 14, family = "Open Sans"))

line

Reorganize plot to show time since entry into HIV care on the x-axis.

# Calendar time as timescale
line2 <- ggplot() +
  geom_segment(data = dat %>% filter(y==0), aes(x = 0, y = id, xend = t, yend = id),  arrow = arrow(length = unit(0.1, "cm"))) +
  geom_segment(data = dat %>% filter(y==1), aes(x = 0, y = id, xend = t, yend = id)) +
  scale_y_continuous(name = "ID", breaks = c(1, 5, 10, 15, 20), limits = c(0,20))+
  scale_x_continuous(name = "Calendar Time", breaks=c(0, 1, 2, 3, 4, 5), limits = c(0, 6)) +
  geom_point(data = dat %>% filter(y==1), aes(x = t, y = id), color = "red", size = 0.6) +
  theme(text = element_text(size = 14, family = "Open Sans"))

line2

Example data (similar to Cole & Hudgens 2010)

Next, we read in some sample data similar to that used in Cole & Hudgens 2010.

##   int     year        w        t cenyear d late newid yearw    yeart
## 1   1 2010.320 4.679838 5.527338    2020 1    1     1  2015 2015.848
## 2   1 2010.321 4.678720 9.557808    2020 1    1     2  2015 2019.879
## 3   1 2010.427 4.573213 9.573213    2020 0    1     3  2015 2020.000
## 4   1 2010.509 4.490943 9.490943    2020 0    1     4  2015 2020.000
## 5   1 2010.645 4.355168 9.355168    2020 0    1     5  2015 2020.000
## 6   1 2010.775 4.224887 9.224887    2020 0    1     6  2015 2020.000

Calendar timescale

### Create second dataset with only events ------
exdat2 <- exdat[exdat$d == 1, ]

### Plot the lines -----
line <- ggplot(data = exdat) +
  geom_segment(aes(x = year, y = newid, xend = yearw, yend = newid), lty = "dotted") +
  geom_segment(aes(x = yearw, y = newid, xend = yeart, yend = newid)) +
  ylab("ID") +
  scale_x_continuous(name = "Calendar Time", breaks=c(2010, 2015,  2020)) +
  geom_point(data = exdat2, aes(x = yeart, y = newid), color = "red", size = 0.5) +
  theme(text = element_text(size = 16, family = "Open Sans"))

line

Time since AIDS diagnosis

line2 <- ggplot(data = exdat) +
  geom_segment(aes(x = 0, y = newid, xend = w, yend = newid), lty = "dotted") +
  geom_segment(aes(x = w, y = newid, xend = t, yend = newid)) +
  ylab("ID") +
  scale_x_continuous(name = "Time since AIDS diagnosis", breaks = c(0,2, 4, 6, 8, 10)) +
  geom_point(data = exdat2, aes(x = t, y = newid), color = "red", size = 0.5) +
  
  theme(text = element_text(size = 14, family = "Open Sans"))

line2