nap {scan} | R Documentation |
Nonoverlap of all Pairs
Description
The nap()
function calculates the nonoverlap of all pairs (NAP; Parker &
Vannest, 2009). NAP summarizes the overlap between all pairs of phase A and
phase B data points. If an increase of phase B scores is expected, a
non-overlapping pair has a higher phase B data point. The NAP equals
number of pairs showing no overlap / number of pairs. Because NAP can
only take values between 50 and 100 percent, a rescaled and therefore more
intuitive NAP (0-100\
Usage
nap(data, dvar, pvar, decreasing = FALSE, phases = c(1, 2))
Arguments
data |
A single-case data frame. See |
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. |
decreasing |
If you expect data to be lower in the B phase, set
|
phases |
A vector of two characters or numbers indicating the two phases
that should be compared. E.g., |
Value
nap |
A data frame with NAP and additional values for each case. |
N |
Number of cases. |
Author(s)
Juergen Wilbert
References
Parker, R. I., & Vannest, K. (2009). An improved effect size for single-case research: Nonoverlap of all pairs. Behavior Therapy, 40, 357-367.
See Also
Other overlap functions:
cdc()
,
overlap()
,
pand()
,
pem()
,
pet()
,
pnd()
,
tau_u()
Examples
## Calculate NAP for a study with lower expected phase B scores
## (e.g. aggressive behavior)
gretchen <- scdf(c(A = 12, 14, 9, 10, B = 10, 6, 4, 5, 3, 4))
nap(gretchen, decreasing = TRUE)
## Request NAP for all cases from the Grosche2011 scdf
nap(Grosche2011)