Testing marginal homogeneity of a continuous bivariate distribution with possibly incomplete paired data
- We discuss the testing problem of homogeneity of the marginal distributions of a continuous bivariate distribution based on a paired sample with possibly missing components (missing completely at random). Applying the well-known two-sample Crámer–von-Mises distance to the remaining data, we determine the limiting null distribution of our test statistic in this situation. It is seen that a new resampling approach is appropriate for the approximation of the unknown null distribution. We prove that the resulting test asymptotically reaches the significance level and is consistent. Properties of the test under local alternatives are pointed out as well. Simulations investigate the quality of the approximation and the power of the new approach in the finite sample case. As an illustration we apply the test to real data sets.
| Author: | Daniel Gaigall |
|---|---|
| DOI: | https://doi.org/10.1007/s00184-019-00742-5 |
| ISSN: | 1435-926X |
| Parent Title (English): | Metrika |
| Publisher: | Springer |
| Document Type: | Article |
| Language: | English |
| Year of Completion: | 2020 |
| Date of first Publication: | 2019/09/03 |
| Date of the Publication (Server): | 2023/01/16 |
| Tag: | Crámer–von-Mises distance; Incomplete data; Marginal homogeneity test; Paired sample; Resampling test |
| Volume: | 2020 |
| Issue: | 83 |
| First Page: | 437 |
| Last Page: | 465 |
| Link: | https://doi.org/10.1007/s00184-019-00742-5 |
| Zugriffsart: | weltweit |
| Institutes: | FH Aachen / Fachbereich Medizintechnik und Technomathematik |
| collections: | Verlag / Springer |
