mc_heatmap: Plot a heatmap or traffic light plot of 'metaconfoundr()'...

In metaconfoundr: Visualize 'Confounder' Control in Meta-Analyses

Plot a heatmap or traffic light plot of metaconfoundr() summaries

Description

mc_heatmap() and mc_trafficlight() visualize the results of metaconfoundr(), summarizing the quality of confounder control in each study.

Usage

mc_heatmap(
  .df,
  legend_title = "control quality",
  sort = FALSE,
  by_group = FALSE,
  score = c("adequate", "sum", "controlled"),
  non_confounders = FALSE
)

mc_trafficlight(
  .df,
  size = 8,
  legend_title = "control quality",
  sort = FALSE,
  by_group = FALSE,
  score = c("adequate", "sum", "controlled"),
  non_confounders = FALSE
)

Arguments

.df	A data frame, usually the result of metaconfoundr()
legend_title	The legend title
sort	Logical. Sort by confounder score? Calculated by score_control()
by_group	Logical. If sorted, sort within domain?
score	The approach used to calculate the score. adequate tests if the study controlled at a strictly adequate level. sum treats control_quality as an ordinal integer, summing it's values such that a higher score has better control overall. controlled tests if any control, including some concerns control, is present.
non_confounders	Logical. Include non-confounders? Default is FALSE.
size	The size of the points in the traffic light plot

Value

a ggplot

See Also

Other plots: facet_constructs(), geom_cochrane(), scale_fill_cochrane(), theme_mc()

Examples

ipi %>%
  metaconfoundr() %>%
  dplyr::mutate(variable = stringr::str_wrap(variable, 10)) %>%
  mc_heatmap() +
  theme_mc() +
  facet_constructs() +
  ggplot2::guides(x = ggplot2::guide_axis(n.dodge = 2))

ipi %>%
  metaconfoundr() %>%
  mc_trafficlight() +
  geom_cochrane() +
  facet_constructs() +
  scale_fill_cochrane() +
  theme_mc() +
  ggplot2::guides(x = ggplot2::guide_axis(n.dodge = 2))

metaconfoundr documentation built on Jan. 18, 2023, 1:10 a.m.