You may want to have multiple CI columns, with each representing a
different outcome. To achieve this, provide a vector of column positions
where the CIs will be drawn. If the number of CI columns matches the
number of est values, one CI will be drawn in each
specified column. If there are fewer CI columns than est
values, the extra est values will be treated as a group and
drawn sequentially in the available CI columns. In this case, the group
number is determined by dividing the number of est values
by the number of ci_column, and multiple CIs will be drawn
in a single cell. As shown in the example below, the CIs are drawn in
columns 3 and 5, with the first and second elements of est,
lower, and upper corresponding to columns 3
and 5, respectively.
In an example with multiple groups, two or more CIs can be displayed
in one cell. The solution is to provide all values sequentially to
est, lower, and upper. This means
that the first n elements in est,
lower, and upper are treated as the same
group, and the same applies to the next n elements, where
n is determined by the number of ci_column. As
demonstrated in the example below, est_gp1 and
est_gp2 are drawn in columns 3 and 5 as group
1, while est_gp3 and est_gp4 are
drawn in the same columns as group 2.
dt <- read.csv(system.file("extdata", "example_data.csv", package = "forestploter"))
dt <- dt[1:7, ]
# Indent the subgroup if there is a number in the placebo column
dt$Subgroup <- ifelse(is.na(dt$Placebo),
dt$Subgroup,
paste0(" ", dt$Subgroup))
# Replace NA with blank or NA will be transformed to character
dt$n1 <- ifelse(is.na(dt$Treatment), "", dt$Treatment)
dt$n2 <- ifelse(is.na(dt$Placebo), "", dt$Placebo)
# Add two blank columns for CI
dt$`CVD outcome` <- paste(rep(" ", 20), collapse = " ")
dt$`COPD outcome` <- paste(rep(" ", 20), collapse = " ")
# Generate point estimation and 95% CI. Paste two CIs together and separate by line break.
dt$ci1 <- paste(sprintf("%.1f (%.1f, %.1f)", dt$est_gp1, dt$low_gp1, dt$hi_gp1),
sprintf("%.1f (%.1f, %.1f)", dt$est_gp3, dt$low_gp3, dt$hi_gp3),
sep = "\n")
dt$ci1[grepl("NA", dt$ci1)] <- "" # Any NA to blank
dt$ci2 <- paste(sprintf("%.1f (%.1f, %.1f)", dt$est_gp2, dt$low_gp2, dt$hi_gp2),
sprintf("%.1f (%.1f, %.1f)", dt$est_gp4, dt$low_gp4, dt$hi_gp4),
sep = "\n")
dt$ci2[grepl("NA", dt$ci2)] <- ""
# Set-up theme
tm <- forest_theme(base_size = 10,
refline_gp = gpar(lty = "solid"),
ci_pch = c(15, 18),
ci_col = c("#377eb8", "#4daf4a"),
footnote_gp = gpar(col = "blue"),
legend_name = "Group",
legend_value = c("Trt 1", "Trt 2"),
vertline_lty = c("dashed", "dotted"),
vertline_col = c("#d6604d", "#bababa"),
# Table cell padding, width 4 and heights 3
core = list(padding = unit(c(4, 3), "mm")))
p <- forest(dt[, c(1, 19, 23, 21, 20, 24, 22)],
est = list(dt$est_gp1,
dt$est_gp2,
dt$est_gp3,
dt$est_gp4),
lower = list(dt$low_gp1,
dt$low_gp2,
dt$low_gp3,
dt$low_gp4),
upper = list(dt$hi_gp1,
dt$hi_gp2,
dt$hi_gp3,
dt$hi_gp4),
ci_column = c(4, 7),
ref_line = 1,
vert_line = c(0.5, 2),
nudge_y = 0.4,
theme = tm)
plot(p)
