Description Usage Arguments Details Value References Examples
View source: R/nonoverlapmeasures.R
Calculates the nonoverlap of all pairs index (Parker & Vannest, 2009).
1 2 3 4 5 6 7 8 9 10 
A_data 
vector of numeric data for A phase. Missing values are dropped. 
B_data 
vector of numeric data for B phase. Missing values are dropped. 
condition 
vector identifying the treatment condition for each observation in the series. 
outcome 
vector of outcome data for the entire series. 
baseline_phase 
character string specifying which value of

improvement 
character string indicating direction of improvement. Default is "increase". 
SE 
character value indicating which formula to use for calculating the
standard error of NAP, with possible values 
confidence 
confidence level for the reported interval estimate. Set to

NAP is calculated as the proportion of all pairs of one observation from each phase in which the measurement from the B phase improves upon the measurement from the A phase, with pairs of data points that are exactly tied being given a weight of 0.5. The range of NAP is [0,1], with a null value of 0.5.
The unbiased variance estimator was described by Sen (1967) and Mee (1990). The Hanley estimator was proposed by Hanley and McNeil (1982). The null variance is a known function of sample size, equal to the exact sampling variance when the null hypothesis of no effect holds. When the null hypothesis does not hold, the null variance will tend to overestimate the true sampling variance of NAP.
The confidence interval for NAP is calculated based on the symmetrized scoreinversion method (Method 5) proposed by Newcombe (2006).
A data.frame containing the estimate, standard error, and/or confidence interval.
Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143, 29–36. doi:doi: 10.1148/radiology.143.1.7063747
Mee, W. (1990). Confidence intervals for probabilities and tolerance regions based on a generalization of the MannWhitney statistic. Journal of the American Statistical Association, 85(411), 793–800. doi:doi: 10.1080/01621459.1990.10474942
Newcombe, R. G. (2006). Confidence intervals for an effect size measure based on the MannWhitney statistic. Part 2: Asymptotic methods and evaluation. Statistics in Medicine, 25(4), 559–573. doi:doi: 10.1002/sim.2324
Parker, R. I., & Vannest, K. J. (2009). An improved effect size for singlecase research: Nonoverlap of all pairs. Behavior Therapy, 40(4), 357–67. doi:doi: 10.1016/j.beth.2008.10.006
Sen, P. K. (1967). A note on asymptotically distributionfree confidence bounds for PX<Y, based on two independent samples. The Annals of Mathematical Statistics, 29(1), 95102. https://www.jstor.org/stable/25049448
1 2 3 4 5 6 7 8 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.