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Plot the population attributable fraction or the potential impact fraction

plot.pif_class.Rd

Creates a ggplot2::ggplot() object containing information on the population attributable fraction or the potential impact fraction.

Usage

# S3 method for pif_class
plot(
  x,
  ...,
  xaxis = c("relative_risk", "counterfactual"),
  title = NULL,
  relative_risks = NULL,
  counterfactuals = NULL
)

Arguments

x

A pif_class object

...

Additional (currently unused) parameters

xaxis

Element for the x axis: counterfactual or relative_risk

title

The title of the plot

relative_risks

Vector of relative risk names to plot (set to NULL to plot all)

counterfactuals

Vector of counterfactual names to plot (set to NULL to plot all)

Value

A ggplot2 object with an image of the pif (or paf)

Examples

# EXAMPLE 1
# Setup the survey design
data(ensanut)
options(survey.lonely.psu = "adjust")
design <- survey::svydesign(data = ensanut, ids = ~1, weights = ~weight, strata = ~strata)

# Calculate two different relative risks
rr <- list(
 function(X, theta) {exp(theta[1] * X[, "systolic_blood_pressure"] / 100)},
 function(X, theta) {exp(theta[2] * X[, "systolic_blood_pressure"] / 100 + theta[3]* X[,"age"])}
)

# Calculate three counterfactual scenarios of SBP reduction from 1 to 3 mmhg
cft <- list(
function(X){X[, "systolic_blood_pressure"]  <- X[, "systolic_blood_pressure"]  - 1; return(X)},
function(X){X[, "systolic_blood_pressure"]  <- X[, "systolic_blood_pressure"]  - 2; return(X)},
function(X){X[, "systolic_blood_pressure"]  <- X[, "systolic_blood_pressure"]  - 3; return(X)}
)

my_pif <- pif(design,
  theta = log(c(1.05, 1.38, 1.21)), rr, cft,
  additional_theta_arguments = c(0.01, 0.03, 0.025),
  n_bootstrap_samples = 10,
)
plot(my_pif)

plot(my_pif, xaxis = "counterfactual")