pipe: Pipe bias functions

In dhaine/episensr: Basic Sensitivity Analysis of Epidemiological Results

Pipe bias functions

Description

episensr also uses the pipe function, %>% to turn function composition into a series of imperative statements.

Arguments

lhs, rhs

Data or bias function and a function to apply to it

Examples

# Instead of
misclassification(matrix(c(118, 832, 103, 884),
dimnames = list(c("BC+", "BC-"), c("AD+", "AD-")), nrow = 2, byrow = TRUE),
type = "exposure", bias_parms = c(.56, .58, .99, .97))
# you can write
dat <- matrix(c(118, 832, 103, 884),
dimnames = list(c("BC+", "BC-"), c("AD+", "AD-")), nrow = 2, byrow = TRUE)
dat %>% misclassification(., type = "exposure", bias_parms = c(.56, .58, .99, .97))
# also for multiple bias:
dat %>%
misclassification(., type = "exposure", bias_parms = c(.56, .58, .99, .97)) %>%
multiple.bias(., bias_function = "selection", bias_parms = c(.73, .61, .82, .76))

dhaine/episensr documentation built on March 18, 2024, 4:54 p.m.