On the multivariate spatial median for clustered data
β Scribed by Jaakko Nevalainen; Denis Larocque; Hannu Oja
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- French
- Weight
- 957 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0319-5724
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
This paper focuses on the analysis of clustered multivariate binary data that arise from developmental toxicity studies. In these studies, pregnant mice are exposed to chemicals to assess possible adverse eects on developing fetuses. Multivariate binary outcomes arise when each fetus in a litter is
Clustered data are the rule in many clinical specialties such as ophthalmology. Methods have been developed for the treatment of clustered continuous or binary outcome data. Less attention has been given to ordinal outcomes which occur frequently in ophthalmology. For example, grading systems of cat
In this paper an exploratory technique based on the diagonalization of crossvariogram matrices is described. Through the definition of a model for the analysis and simulation of multivariate spatial data, a test procedure for the assumption of isotropy of multivariate spatial data is proposed. Appli
McNemar's test is often used to compare two proportions estimated from paired observations. We propose a method extending this to the case where the observations are sampled in clusters. The proposed method is simple to implement and makes no assumptions about the correlation structure. We conducted