Plots a zplot visualization showing the histogram of observed z-statistics overlaid with model-implied densities.
Usage
# S3 method for class 'zplot_brma'
plot(
x,
plot_type = "base",
probs = c(0.025, 0.975),
max_samples = 10000,
plot_fit = TRUE,
plot_extrapolation = TRUE,
plot_ci = TRUE,
plot_thresholds = TRUE,
from = -6,
to = 6,
by.hist = 0.5,
length.out.hist = NULL,
by.lines = 0.05,
length.out.lines = NULL,
dots_hist = NULL,
dots_fit = NULL,
dots_extrapolation = NULL,
dots_thresholds = NULL,
...
)Arguments
- x
a zplot_brma object.
- plot_type
graphics system:
"base"or"ggplot". Defaults to"base".- probs
quantiles for credible intervals. Defaults to
c(.025, .975).- max_samples
maximum posterior samples for density estimation. Defaults to 10000. Use
Infto use all posterior samples.- plot_fit
whether to show fitted density (with bias adjustments). Defaults to
TRUE.- plot_extrapolation
whether to show extrapolated density (bias removed). Defaults to
TRUE.- plot_ci
whether to show credible interval bands. Defaults to
TRUE.- plot_thresholds
whether to show significance threshold lines. Defaults to
TRUE.- from, to
z-value range for plotting. Defaults to
-6and6.- by.hist
bin width for histogram. Defaults to 0.5.
- length.out.hist
number of histogram bins (alternative to
by.hist).- by.lines
step size for density lines. Defaults to 0.05.
- length.out.lines
number of density points (alternative to
by.lines).- dots_hist
graphical parameters for histogram (list).
- dots_fit
graphical parameters for fit lines (list).
- dots_extrapolation
graphical parameters for extrapolation lines (list).
- dots_thresholds
graphical parameters for threshold lines (list).
- ...
additional graphical parameters passed to components.
Details
The plot displays two density curves:
- Fit (black)
Model-implied density including publication bias adjustments. This represents the expected distribution of z-statistics given the estimated selection process.
- Extrapolation (blue)
Bias-corrected curve representing the hypothetical distribution without selective reporting, scaled by the expected suppressed studies under selection models. This curve is not normalized to integrate to one when selection implies missing studies.