Funnel Plots with MAIVE

Overview

get_funnel_plot() draws a base-graphics funnel plot using the original meta-analysis inputs and a fitted MAIVE/WAIVE result. Device management (e.g., png(), svg(), pdf(), base64 encoding) is left to you so you can embed the graphic wherever you need.

For a guided, interactive workflow, visit https://www.easymeta.org.

What it shows:

• Confidence-region shading (90/95/99%) built from the simple mean
• Simple-mean vertical line vs MAIVE/WAIVE fit line (with optional CI)
• Raw points (effect vs standard error) plus instrumented/adjusted points when available
• Optional WAIVE point-size scaling reflecting downweighting

Required inputs

get_funnel_plot(dat, result, instrument = NULL, model_type = "MAIVE")

• dat: data frame with numeric bs (effect sizes) and sebs (standard errors, > 0)
• result: list returned by maive() or waive()
• instrument: optional 0/1 to control whether adjusted SEs/weights are used; if NULL, inferred from result
• model_type: label for plot text/legend (e.g., "MAIVE" or "WAIVE")

Minimal synthetic example (quick to run)

The code below is set to eval = FALSE to keep the vignette fast. Run it interactively to produce the plot.

library(MAIVE)

set.seed(123)
n <- 40
dat <- data.frame(
  bs = rnorm(n, mean = 0.2, sd = 0.25),
  sebs = runif(n, min = 0.05, max = 0.3),
  Ns = sample(80:800, n, replace = TRUE),
  study_id = rep(1:10, each = 4)
)

# Fit MAIVE (instrumented PET-PEESE, no weights, cluster-robust, wild bootstrap)
res <- maive(
  dat = dat,
  method = 3,
  weight = 0,
  instrument = 1,
  studylevel = 2,
  SE = 3,
  AR = 1
)

# Draw to the current device
get_funnel_plot(dat = dat, result = res, model_type = "MAIVE")

Saving to file (PNG example)

Device control is up to you; this pattern works for PNG. Replace png() with svg()/pdf() as needed.

png("maive-funnel.png", width = 1800, height = 1400, res = 200)
get_funnel_plot(dat = dat, result = res, model_type = "MAIVE")
dev.off()

Interpreting the plot

• Shaded cones: 90/95/99% reference regions centered on the simple mean; darker shading indicates more extreme p-values.
• Vertical lines: dashed at zero, dotted for the simple mean, solid for MAIVE/WAIVE fit (with dashed CI if slope info is available).
• Points: hollow circles for raw effects; filled circles for instrumented/adjusted SEs when instrument = 1.
• Point size (WAIVE): when WAIVE provides weights, adjusted points shrink in proportion to downweighting.
• Legend: shows base points, adjusted points, MAIVE/WAIVE fit, and 95% CI for the fit when present.

Tips and edge cases

• If instrument = 0 or the result lacks SE_instrumented, the plot omits adjusted points and uses only raw SEs.
• WAIVE weights are optional; when absent, adjusted points use the default size.
• Slope metadata is drawn when available (linear/quadratic/kink). If not present, the fit line is omitted.
• Ensure dat$sebs are strictly positive and finite; the helper validates inputs and will stop otherwise.
• Axis padding and tick formatting are automatic, but you can wrap the call in your own device settings to control size/resolution.

See also

• vignette("introduction", package = "MAIVE") for full estimator workflow
• Function reference: ?get_funnel_plot, ?maive, ?waive