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 where ties are
counted as half non-overlaps. Because NAP can take values between 0 and 100
percent where values below 50 percent indicate an inverse effect, an nap
rescaled from -100 to 100 percent where negative
values indicate an inverse effect is also displayed (\(nap_{rescaled} = 2
* nap - 100\)).
Usage
nap(data, dvar, pvar, decreasing = FALSE, phases = c(1, 2))
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.
- decreasing
If you expect data to be lower in the B phase, set
decreasing = TRUE
. Default isdecreasing = FALSE
.- phases
A vector of two characters or numbers indicating the two phases that should be compared. E.g.,
phases = c("A","C")
orphases = 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 isphases = c(1,2)
.
References
Parker, R. I., & Vannest, K. (2009). An improved effect size for single-case research: Nonoverlap of all pairs. Behavior Therapy, 40, 357-367.
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)
#> Nonoverlap of All Pairs
#>
#> Case NAP NAP Rescaled w p d R²
#> Case1 94 88 22 <.05 2.2 0.56
## Request NAP for all cases from the Grosche2011 scdf
nap(Grosche2011)
#> Nonoverlap of All Pairs
#>
#> Case NAP NAP Rescaled w p d R²
#> Eva 69 38.5 24 .10 0.747 0.1223
#> Georg 48 -4.2 62 .57 -0.072 0.0013
#> Olaf 45 -10.4 53 .66 -0.176 0.0077