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Selection-Function Plot for Publication-Bias Models

selection_plot.Rd

Draws the estimated selection function (selection weight versus p-value) from a fitted pub_bias object.

Usage

selection_plot(object, ...)

# S3 method for class 'pub_bias'
selection_plot(
  object,
  normalize = TRUE,
  p_grid = seq(0.001, 0.999, length.out = 200),
  line_col = "#C0392B",
  line_lwd = 2,
  bar_col = "#F3A683",
  border_col = "#B23A2B",
  xlab = "P-value",
  ylab = NULL,
  main = "Estimated Selection Function",
  main_adj = 0.5,
  main_line = NULL,
  ...
)

# S3 method for class 'pub_bias'
plot(x, type = c("funnel", "selection"), ...)

Arguments

object

A fitted object returned by publication_bias.

...

Additional arguments passed to funnel_plot() or selection_plot().

normalize

Logical; if TRUE, rescales weights so the largest plotted weight equals 1.

p_grid

Numeric vector of p-values where the selection function is evaluated for continuous methods.

line_col

Line color used for continuous selection models.

line_lwd

Line width used for continuous selection models.

bar_col

Fill color used for bin bars when method = "beta_binomial".

border_col

Border color for bin bars.

xlab

X-axis label.

ylab

Optional y-axis label.

main

Plot title.

main_adj

Horizontal title alignment in [0, 1].

main_line

Optional title line. If NULL, default is used.

x

A fitted object returned by publication_bias().

type

Plot type: "funnel" or "selection".

Value

Invisibly returns the plotting data frame.

Examples

if (FALSE) { # \dontrun{
fit <- mars(
  data = teacher_expectancy,
  studyID = "study",
  effectID = NULL,
  sample_size = NULL,
  formula = yi ~ 1,
  variance = "vi",
  varcov_type = "univariate",
  structure = "univariate"
)
bias_fit <- publication_bias(fit)
selection_plot(bias_fit)
} # }