pet: Percent exceeding the trend

Description

The pet function returns the percentage of Phase B data points that exceed the prediction based on the Phase A trend. A binomial test against a 50/50 distribution is calculated. It also calculates the percentage of Phase B data points that exceed the upper (or lower) 95 percent confidence interval of the predicted progression.

Usage

pet(data, dvar, pvar, mvar, ci = 0.95, decreasing = FALSE, phases = c(1, 2))

Value


`PET`	Percent exceeding the trend.
`ci`	Width of confidence interval.
`decreasing`	Logical argument from function call (see Arguments above).

Arguments

data: A single-case data frame. See scdf() to learn about this format.
dvar: Character string with the name of the dependent variable. Defaults to the attributes in the scdf file.
pvar: Character string with the name of the phase variable. Defaults to the attributes in the scdf file.
mvar: Character string with the name of the measurement time variable. Defaults to the attributes in the scdf file.
ci: Width of the confidence interval. Default is ci = 0.95.
decreasing: If you expect data to be lower in the B phase, set decreasing = TRUE. Default is decreasing = FALSE.
phases: A vector of two characters or numbers indicating the two phases that should be compared. E.g., phases = c("A","C") or phases = c(2,4) for comparing the second to the fourth phase. Phases could be combined by providing a list with two elements. E.g., phases = list(A = c(1,3), B = c(2,4)) will compare phases 1 and 3 (as A) against 2 and 4 (as B). Default is phases = c(1,2).

Author

Juergen Wilbert

Examples

Run this code


## Calculate the PET and use a 99%-CI for the additional calculation
# create random example data
design <- design(n = 5, slope = 0.2)
dat <- random_scdf(design, seed = 23)
pet(dat, ci = .99)