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Create ECDF Plot for Sensitivity Analysis

Source: R/ecdf_plot.R
ecdf_plot.Rd

Creates an empirical cumulative distribution function (ECDF) plot showing posterior distributions across different sensitivity analyses (All studies, Excluding High RoB, PET-PEESE, Mixture Model, BMA).

Usage

ecdf_plot(
  model,
  data,
  priors,
  measure,
  study_var = NULL,
  rob_var = NULL,
  exclude_high_rob = FALSE,
  incl_pet_peese = FALSE,
  pet_peese_direction = "negative",
  pet_peese_threshold = 0.1,
  incl_mixture = FALSE,
  incl_bma = FALSE,
  model_bma = NULL,
  prob_reference = "null",
  null_value = NULL,
  null_range = NULL,
  add_null_range = FALSE,
  color_null_range = "#77bb41",
  label_control = "Control",
  label_intervention = "Intervention",
  title = NULL,
  subtitle = NULL,
  xlim = NULL,
  x_breaks = NULL,
  color_palette = NULL,
  show_density = TRUE,
  prior_to_plot = "weakreg",
  font = NULL
)

Arguments

model

A fitted brmsfit object from a Bayesian meta-analysis

data

A data frame containing the study data used to fit the model

priors

A named list of brms prior specifications (created with brms::prior()) with names typically including "vague", "weakreg", and "informative"

measure

Character string specifying the effect measure. One of "OR" (odds ratio), "RR" (risk ratio), "HR" (hazard ratio), "IRR" (incidence rate ratio), "MD" (mean difference), or "SMD" (standardized mean difference)

study_var

Optional. Name of the study identifier variable (unquoted). Required if incl_pet_peese = TRUE or incl_mixture = TRUE

rob_var

Optional. Name of the risk of bias variable (unquoted). Should contain values like "Low", "Some concerns", "High"

exclude_high_rob

Logical. If TRUE, performs sensitivity analysis excluding studies with high risk of bias. Default is FALSE

incl_pet_peese

Logical. If TRUE, includes PET-PEESE bias adjustment analysis. Default is FALSE

pet_peese_direction

Character string. Direction of expected bias for PET-PEESE. Either "negative" or "positive". Default is "negative"

pet_peese_threshold

Numeric. Threshold for choosing between PET and PEESE (based on proportion of studies showing effect). Default is 0.10

incl_mixture

Logical. If TRUE, includes robust mixture model analysis. Default is FALSE

incl_bma

Logical. If TRUE, includes Bayesian model averaging results. Default is FALSE

model_bma

Named list of RoBMA model fits (from RoBMA_brms()) to include in model averaging. Names should be "vague", "weakreg", or "informative"

prob_reference

Character string. What reference to use for probability calculations. Either "null" (compare to null_value) or "null_range" (compare to null_range boundaries). Default is "null"

null_value

Numeric. The null value for the effect measure. If NULL, uses default based on measure (1 for ratio measures, 0 for difference measures)

null_range

Numeric vector of length 2 or single numeric value. Defines the range of practical equivalence around the null value.

add_null_range

Logical. If TRUE, displays the null range region on the plot. Default is FALSE

color_null_range

Character string. Color for the null range region. Default is "#77bb41" (green)

label_control

Character string. Label for the control/reference group. Default is "Control"

label_intervention

Character string. Label for the intervention group. Default is "Intervention"

title

Optional character string. Main title for the plot

subtitle

Optional character string. Subtitle for the plot

xlim

Optional numeric vector of length 2. X-axis limits for the plot

x_breaks

Optional numeric vector. Custom x-axis break points

color_palette

Optional named character vector of colors for each section. Names should match section labels (e.g., "All studies", "Excluding High RoB", etc.)

show_density

Logical. If TRUE, includes a density plot below the ECDF. Default is TRUE

prior_to_plot

Character string. Which prior specification to plot in the ECDF. One of "vague", "weakreg", or "informative". Default is "weakreg"

font

Optional character string. Font family to use for the plot

Value

A ggplot object (or patchwork object if show_density = TRUE)

Details

This function creates an ECDF plot that displays the cumulative probability distributions of pooled effects across different sensitivity analyses. The plot includes:

  • Left y-axis: Probability that mean effect < x

  • Right y-axis: Probability that mean effect > x

  • Optional density curves below the ECDF

  • Optional region of practical equivalence (ROPE) shading

The prob_reference argument controls how probabilities are calculated:

  • "null": Probabilities are calculated relative to the null value (e.g., OR = 1)

  • "null_range": Probabilities are calculated relative to the null range boundaries (left y-axis shows P(effect < lower bound), right y-axis shows P(effect > upper bound))

Examples

if (FALSE) { # \dontrun{
# Basic ECDF plot
sensitivity_ecdf_plot(
  model = my_brms_model,
  data = my_data,
  priors = list(
    vague = prior("normal(0, 10)", class = "Intercept"),
    weakreg = prior("normal(0, 1)", class = "Intercept"),
    informative = prior("normal(0.5, 0.5)", class = "Intercept")
  ),
  measure = "OR",
  prior_to_plot = "weakreg"
)

# Advanced ECDF with null range probability reference
sensitivity_ecdf_plot(
  model = my_model,
  data = my_data,
  priors = my_priors,
  measure = "OR",
  study_var = study_id,
  rob_var = rob,
  exclude_high_rob = TRUE,
  incl_pet_peese = TRUE,
  incl_mixture = TRUE,
  incl_bma = TRUE,
  model_bma = my_robma_models,
  prior_to_plot = "weakreg",
  prob_reference = "null_range",
  null_range = c(0.9, 1.1),
  add_null_range = TRUE
)
} # }