aberrantscoreslong {triplesmatch}

Convert outcome to aberrant ranks

Description

Replaces non-aberrant responses by 0 and ranks the aberrant responses by severity. The more aberrant responses have the highest ranks.

Usage

aberrantscoreslong(y, cutoff, cutoff_dir = "less", tau = 0, z = NULL)

Arguments

y

Vector of outcomes. Length is equal to the number of units

cutoff

The cutoff for whether an outcome is aberrant. Any outcome more extreme then this cutoff will be considered aberrant

cutoff_dir

Either 'less' or 'greater', indicating whether outcomes should be aberrant if they are less than the 'cutoff' or greater than the 'cutoff', respectively

tau

The null treatment effect to be subtracted from all treated units before aberrant ranking commences. If 'tau != 0', then 'z' is required

z

Vector with length equal to that of y. Each element specifies whether a unit is treated (1) or not (0)

Details

This function serves the same function as [aberrantscores()] but takes inputs in the 'long' format instead of the 'wide' format (see [formattrip()] for a description of the two formats, their uses, and their creation).

This can be useful for creating a column of 'sc' in [infsentrip()] if the aberrant rank test is desired for that variable.

Value

Vector of aberrant ranks corresponding to 'y'

See Also

aberrantscores for the same function with inputs in the wide format instead of long

formattrip for formatting of the triples match into wide or long format

Examples

# Generate some data
set.seed(316)
n <- 30
x <- rnorm(n, 0, 1)
nt <- floor(n * 0.2)
nc <- n - nt
z <- c(rep(1, nt), rep(0, nc))
# Create a distance matrix (all units in one stratum here)
dist <- dist_mahal(data.frame(x = x), z, rep(1, n))[[1]]
# Conduct the triples match
triplesm <- triples_st(cost = dist, z = z, solver = "rlemon")
# Create primary and negative outcomes with some random unit names
y <- cbind(rnorm(40), runif(40))
rownames(y) <- sample(1:40)
# Reformat the triples match
ylong <- formattrip(m = triplesm, y = y, type = "long")
# Aberrant ranks for primary outcome
y[, 1] <- aberrantscoreslong(y[, 1], cutoff = 0.5, cutoff_dir = "greater")