Tau-U
Tau-U is a rank-based effect-size index for single-case research that combines the degree of nonoverlap between baseline and treatment phases with the trend within phases, and that can optionally subtract out any improving trend already present in the baseline. Developed by Richard Parker, Kimberly Vannest, and colleagues in 2011, it extends the Nonoverlap of All Pairs (NAP) statistic by adding a Kendall-style trend component, giving practitioners a single index that is robust to outliers, has a known sampling distribution for significance testing, and does not unfairly credit a treatment for change that the baseline was already heading toward.
Lasīt pilno metodes aprakstu
Piesakieties ar bezmaksas kontu, lai lasītu šo sadaļu.
Metožu karte
Saistīto metožu apkaime — atlasiet mezglu, lai izpētītu.
Avoti
- Parker, R. I., Vannest, K. J., Davis, J. L., & Sauber, S. B. (2011). Combining nonoverlap and trend for single-case research: Tau-U. Behavior Therapy, 42(2), 284–299. DOI: 10.1016/j.beth.2010.08.006 ↗
- Parker, R. I., & Vannest, K. J. (2009). An improved effect size for single-case research: Nonoverlap of all pairs. Behavior Therapy, 40(4), 357–367. DOI: 10.1016/j.beth.2008.10.006 ↗
Kā citēt šo lapu
ScholarGate. (2026, June 22). Tau-U Nonoverlap Effect Size for Single-Case Research. ScholarGate. https://scholargate.app/lv/social-work/tau-u-single-case
Kura metode?
Novietojiet šo metodi blakus tās tuvākajām radniecīgajām metodēm un lasiet tās līdzās — bibliotēka noliek grāmatas uz galda; izvēle ir jūsu.
- Nonoverlap of All PairsSocial Work↔ salīdzināt
- Percentage of Nonoverlapping DataSocial Work↔ salīdzināt
- Single-System DesignSocial Work↔ salīdzināt
- Visual Analysis of Single-Case DataSocial Work↔ salīdzināt
Uz to atsaucas
Līdzīgas metodes
Pamanījāt kļūdu šajā lapā? Ziņojiet vai ierosiniet labojumu →