Abstract #300791

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JSM 2003 Abstract #300791
Activity Number: 378
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 12:00 PM to 1:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #300791
Title: Confidence Intervals Methods in a Nonparametric Analysis of Covariance
Author(s): Won Sun Chen*+
Companies: University of Kentucky
Address: 3524 Creekwood Dr., Lexington, KY, 40502-3028,
Keywords: confidence interval ; nonparametric method ; analysis of covariance ; dependent data
Abstract:

Langer (1998), Bathke (2002), and Siemer (2002) have introduced a nonparametric, robust alternative to analysis of covariance (ANCOVA) that can be used for dependent data and for data with relatively small sample sizes. Also, the number of covariates to be included into the model is not restricted, and the covariates can be purely ordinal. Based on this alternative ANCOVA, we propose confidence intervals for treatment and covariate effects, thereby in part using a nonparametric bootstrap method. We also use the results to test for a treatment*covariate interaction. The methods are compared to their parametric and semiparametric counterparts, and analysis of a dataset illustrates the application.

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