misclassification: Misclassification

In louisahsmith/simpleSens: What the Package Does (One Line, Title Case)

Description

A type of bias. Declares that (differential) misclassification will be a component of interest in the sensitivity analysis. Generally used within other functions; its output is returned invisibly.

Usage

misclassification(
  ...,
  outcome_rare = NULL,
  exposure_rare = NULL,
  message = FALSE
)

Arguments

...	Arguments describing the type of misclassification. Currently two options: "outcome" or "exposure".
outcome_rare	Logical. Is the outcome rare enough that outcome odds ratios approximate risk ratios? Only needed when considering exposure misclassification.
exposure_rare	Logical. Is the exposure rare enough that exposure odds ratios approximate risk ratios? Only needed when considering exposure misclassification.
message	Logical. If TRUE, returns warnings and messages immediately. Defaults to FALSE because it is generally used within the calculate_evalue() or calculate_bound() functions, which will print the same messages/warnings.

Value

Invisibly returns a list with components whose values depend on the options chosen: n (the degree of the polynomial in the numerator), d (the degree of the polynomial in the denominator), m (the parameters in the bias factor), mess (any messages/warnings that should be printed for the user), and bias("misclassification").

Examples

misclassification("exposure", outcome_rare = TRUE, exposure_rare = FALSE)
output <- misclassification("outcome")
output

# Calculate an E-value for misclassification
calculate_evalue(RRobs = 4,
         biases = misclassification("exposure",
                  outcome_rare = TRUE, exposure_rare = TRUE))

louisahsmith/simpleSens documentation built on March 19, 2020, 12:07 a.m.