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A character vector with the title for the overall plot (applied to the top plot internally).

Source: R/spec_curve.R
spec_curve.Rd

Specification Curve Analysis

Usage

spec_curve(
  x,
  focal = NULL,
  yvar = NULL,
  p.adjusted = NULL,
  alpha = 0.05,
  tbr = c(0.4, 0.6),
  colors = NULL,
  shapes = NULL,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  top.theme = NULL,
  bottom.theme = NULL,
  redundant = TRUE,
  conf.int = FALSE
)

Arguments

x

an object of class `pima`, usually the result of the `pima()` function.

yvar

character indicating the column of the `x$summary_table` object to be used in the y axes of the top part of the specification curve (usually the estimated parameter). Default to `"Estimate"`.

alpha

A numeric value specifying the significance level for the confidence intervals. Default is 0.05.

tbr

A numeric vector of two elements indicating the proportion of space assigned to the top and bottom part of the plot.

colors

A character vector of two elements with the colors for the point representing non-significant and significant p-values.

xlab

a character vector for the x axis title. Default to "Specification"

ylab

a character vector for the y axis title of the top plot. Default to `yvar`.

top.theme

a function with a `ggplot2` compatible theme for the top plot. Default to ggplot2::theme_minimal()`

bottom.theme

a function with a `ggplot2` compatible theme for the bottom plot Default to `ggplot2::theme_minimal()`

p.values

character indicating the column of the `x$summary_table` object with the p values. Default to `""p.adj.maxT"` (maxT corrected p values).

A

character vector of two elements with the shapes representing non-significant and significant p-values. Default to simple points.

Value

A plot displaying the specification curve with confidence intervals and p-values, as well as a legend showing the variable combinations used in each specification. The output object is a [`patchwork`] object thus a collection of `ggplot2` objects. The underlying datasets can be accessed using `@data` for each plot.

Details

This function performs a specification curve analysis based on the results of a set of regression models. It visualizes the coefficient estimates with confidence intervals, p-values, and highlights significant specifications.

Examples

# Example usage (assuming `res` is a pre-computed result object):
# spec_curve(res, alpha = 0.05)