Add a summary table to a forest plot — add_forest

Compose a summary table onto a forest plot.

Usage

add_forest_table(
  plot = NULL,
  position = c("left", "right"),
  columns = NULL,
  term_header = "Term",
  n_header = "N",
  events_header = "Events",
  estimate_label = NULL,
  p_header = "P-value",
  column_labels = NULL,
  digits = NULL,
  estimate_digits = NULL,
  interval_digits = NULL,
  p_digits = NULL,
  estimate_fmt = NULL,
  ci_fmt = NULL,
  text_size = NULL,
  header_text_size = NULL,
  header_fontface = "bold",
  header_family = NULL,
  striped_rows = NULL,
  stripe_fill = NULL,
  stripe_colour = NULL,
  stripe_alpha = NULL,
  grid_lines = FALSE,
  grid_line_colour = "black",
  grid_line_size = 0.3,
  grid_line_linetype = 1
)

Arguments

plot: A plot created by ggforestplot(). Leave as NULL to use + add_forest_table(...) syntax.
position: Whether to place the table on the left or right of the forest plot.
columns: Optional explicit columns to display in the side table, in the order they should appear. Accepts built-in names such as "term", "n", "events", "estimate", "ci", and "p", arbitrary original dataframe columns, or numeric positions in the supplied data. "conf.low" and "conf.high" are accepted as aliases for "ci".
term_header: Header text for the term column.
n_header: Header text for the N column.
events_header: Header text for the Events column.
estimate_label: Header label for the estimate column. Defaults to the model-derived label when available.
p_header: Header text for the p-value column.
column_labels: Optional named vector used to relabel table column headers. Names should match values supplied to columns after column resolution, such as "term", "estimate", "ci", "p", or an arbitrary original dataframe column.
digits: Deprecated. Number of digits used when formatting estimates and p-values. Defaults to 2. Use estimate_digits, interval_digits, and p_digits for separate control.
estimate_digits: Number of digits used for point estimates.
interval_digits: Number of digits used for confidence interval bounds.
p_digits: Number of digits used for p-values.
estimate_fmt: Format string for the estimate column. Use {estimate}, {conf.low}, and {conf.high} as placeholders. The shorthand {conf.low, conf.high} is also supported. Defaults to "{estimate} ({conf.low}, {conf.high})", or "{estimate}" when columns includes "ci".
ci_fmt: Format string for the confidence interval column when columns includes "ci". Use {conf.low} and {conf.high} as placeholders. The shorthand {conf.low, conf.high} is also supported. Defaults to "({conf.low}, {conf.high})".
text_size: Text size for table contents. Defaults to 3.2.
header_text_size: Header text size for table column labels. Defaults to 11.
header_fontface: Font face used for table column labels. Defaults to "bold".
header_family: Optional font family used for table column labels.
striped_rows: Whether to draw alternating row stripes behind the table. Defaults to the stripe setting used in ggforestplot().
stripe_fill: Fill colour used for striped rows. Defaults to the stripe fill used in ggforestplot().
stripe_colour: Outline colour for striped rows. Defaults to the stripe outline used in ggforestplot().
stripe_alpha: Transparency for striped rows. Defaults to the stripe alpha used in ggforestplot().
grid_lines: Whether to draw black horizontal grid lines in the table.
grid_line_colour: Colour used for the table grid lines.
grid_line_size: Line width used for the table grid lines.
grid_line_linetype: Line type used for the table grid lines.

Value

A patchwork-composed plot containing the forest plot and side table, or a ggplot add-on object when plot = NULL.

Examples

coefs <- data.frame(
  term = c("Age", "BMI", "Treatment"),
  estimate = c(0.3, -0.2, 0.4),
  conf.low = c(0.1, -0.4, 0.2),
  conf.high = c(0.5, 0.0, 0.6),
  sample_size = c(120, 115, 98),
  p_value = c(0.012, 0.031, 0.004)
)

p <- ggforestplot(coefs, n = "sample_size", p.value = "p_value")
add_forest_table(
  p,
  position = "left",
  columns = c("term", "n", "estimate", "p"),
  estimate_label = "Beta"
)


ggforestplot(coefs, n = "sample_size", p.value = "p_value") +
  add_forest_table(
    position = "right",
    columns = c("term", "n", "estimate", "p"),
    estimate_label = "Beta"
  )