Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Jacqueline L. Johnson, Keith E. Muller, James C. Slaughter, Matthew J. Gurka, Matthew J. Gribbin, Sean L. Simpson
Title: POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models
Abstract: The POWERLIB SAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the "univariate" approach to repeated measures (UNIREP), the Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda tests in "multivariate" approach (MULTIREP), as well as a limited but useful range of mixed models. The familiar univariate linear model with Gaussian errors is an important special case. For estimated covariance, the software provides confidence limits for the resulting estimated power. All power and confidence limits values can be output to a SAS dataset, which can be used to easily produce plots and tables for manuscripts.

Page views:: 7787. Submitted: 2007-11-26. Published: 2009-04-29.
Paper: POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models     Download PDF (Downloads: 8356)
Supplements:
POWERLIB21.IML: SAS/IML source code Download (Downloads: 1371; 218KB)
v30i05-examples.zip: Input and output files for examples from the paper Download (Downloads: 1065; 92KB)
exk01.sd2: SAS example data set Download (Downloads: 1018; 64KB)
p0104.sd2: SAS example data set Download (Downloads: 1026; 4KB)

DOI: 10.18637/jss.v030.i05

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.