Affordable Access

Publisher Website

Multiple comparisons with a control in repeated measures incomplete block designs usingR-estimators

Authors
Journal
Journal of Statistical Planning and Inference
0378-3758
Publisher
Elsevier
Publication Date
Volume
70
Issue
2
Identifiers
DOI: 10.1016/s0378-3758(97)00191-2
Keywords
  • Control Treatment
  • Dispersion Function
  • Multiple Comparisons
  • R-Estimators
Disciplines
  • Design
  • Medicine

Abstract

Abstract New multiple comparison with a control (MCC) procedures are developed in repeated measures incomplete block design settings based on R-estimates. It is assumed that the errors within each subject are exchangeable random variables. The R-estimators of the treatment effects are obtained by minimizing a sum of Jaeckel (1972)-type dispersion functions. Based on the R-estimators, Dunnett-type multiple comparison procedures are developed for comparing test-treatments with a control-treatment. Under exchangeable errors, it is demonstrated that for Cox-type designs, the new procedures are more efficient than the existing nonparametric procedures. The new MCC procedures are applied to a data set in a clinical trial which consists of patients with reversible obstructive pulmonary disease.

There are no comments yet on this publication. Be the first to share your thoughts.