Rank‐based procedures in factorial designs: hypotheses about non‐parametric treatment effects
By Edgar Brunner, Frank Konietschke, Markus Pauly, Madan Lal Puri. 2016
111 citations recorded by the source corpus.
Existing tests for factorial designs in the non‐parametric case are based on hypotheses formulated in terms of distribution functions. Typical null hypotheses, however, are formulated in terms of some parameters or effect measures, particularly in heteroscedastic settings. Here this idea is extended to non‐parametric models by introducing a novel non‐parametric analysis‐of‐variance type of statistic based on ranks or pseudoranks which is suitable for testing hypotheses formulated in meaningful non‐parametric treatment effects in general factorial designs. This is achieved by a careful detailed study of the common distribution of rank‐based estimators for the treatment effects. Since the statistic is asymptotically not a pivotal quantity we propose three different approximation techniques, discuss their theoretic properties and compare them in extensive simulations together with two additional Wald‐type tests. An extension of the presented idea to general repeated measures designs is briefly outlined. The rank‐ and pseudorank‐based procedures proposed maintain the preassigned type I error rate quite accurately, also in unbalanced and heteroscedastic models.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/74852c0af8b19c39a803a2695ccaf3fa3279ce60
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
In Statistics and Probability
Citations in the corpus
- Randomization Tests for Weak Null Hypotheses in Randomized Experiments (2018, background): “epend on the outcome values under Fisher’s sharp null hypothesis (Lehmann 1975; Rosenbaum 2002a). They are useful for testing some weak null hypotheses (Brunner and Puri 2001; Chung and Romano 2016a; Brunner et al. 2017; Umlauft et al. 2017). However, it is not entirely clear what causal effects the”