Multivariate non-parametric tests of trend when the data are incomplete
In environmental and medical studies, multivariate data are often recorded over regular time intervals and examined for monotone increasing or decreasing trends in one or more of the variables. Dietz and Killeen (J. Amer. Statist. Assoc. 76 (1981) 169) proposed a non-parametric test based on the Kendall measure of correlation and applied it to medical data. In this paper, we are concerned with situations when the data are partially incomplete. New test statistics based on the Spearman and Kendall correlation coefficients are proposed which are shown to be asymptotically chi squared. Results from a limited simulation study reveal that in most situations, the proposed test statistic performs better than its counterpart which deletes the missing data.
Volume (Year): 57 (2002)
Issue (Month): 3 (April)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Patel, Kantilal M., 1973. "Hájek-Sidák approach to the asymptotic distribution of multivariate rank order statistics," Journal of Multivariate Analysis, Elsevier, vol. 3(1), pages 57-70, March.
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:57:y:2002:i:3:p:281-290. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If references are entirely missing, you can add them using this form.