The pet function provides the percentage of phase B data points
exceeding the prediction based on the phase A trend. A binomial test against
a 50/50 distribution is computed. Furthermore, the percentage of phase B
data points exceeding the upper (or lower) 95 percent confidence interval of
the predicted progress is computed.
Percent
exceeding the upper / lower 95%-CI boundary.
p
P value of Binomial
Test.
ci.percent
Width of confidence interval in percent.
se.factors
Standard error.
N
Number of cases.
decreasing
Logical argument from function call (see Arguments
above).
case.names
Assigned name of single-case.
phases
-
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
See Also
Other overlap functions:
corrected_tau(),
nap(),
overlap(),
pand(),
pem(),
pnd(),
tau_u()
## Calculate the PET and use a 99%-CI for the additional calculation# create random example datadesign <- design(n = 5, slope = 0.2)
dat <- random_scdf(design, seed = 23)
pet(dat, ci = .99)