Abstract #302041

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JSM 2003 Abstract #302041
Activity Number: 446
Type: Contributed
Date/Time: Thursday, August 7, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #302041
Title: Evaluating the Power of Minitab's XLOF Procedure for Testing Lack of Fit in Multiple Linear Regression
Author(s): Daniel Wang*+
Companies: Central Michigan University
Address: Dept. of Mathematics, Mount Pleasant, MI, 48859-0001,
Keywords: Minitab XLOF ; lack of fit ; regression diagnosis ; power ; simulation
Abstract:

Lawrance (1994) discussed Minitab's "data subsetting" lack-of-fit test (XLOF) for data without replicates, an alternative to the classical lack-of-fit test for linear regression models with k predict variables. Evaluating the power of XLOF is impossible since it is based on 2k+1 subtests which are not independent. This study simulates the power of XLOF using Minitab macros for k=2 predictor variables with several forms of curvature and compares this to the power of the classical lack-of-fit test. These comparisons will lead to pragmatic suggestions on when XLOF should be used.

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