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POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models.

Jacqueline L Johnson1, Keith E Muller2, James C Slaughter1

  • 1University of North Carolina at Chapel Hill.

Journal of Statistical Software
|November 18, 2014
PubMed
Summary
This summary is machine-generated.

POWERLIB SAS/IML software offers power calculations for multivariate linear and mixed models. It supports various statistical tests and provides confidence limits for estimated power, aiding in manuscript preparation.

Keywords:
Gaussian errorsmixed modelsmultivariate linear modelspower

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Area of Science:

  • Statistics
  • Statistical Software
  • Biostatistics

Background:

  • Multivariate linear models and mixed models are crucial in statistical analysis.
  • Accurate power calculations are essential for study design and interpretation.
  • Existing software may lack comprehensive options for these models.

Purpose of the Study:

  • To introduce POWERLIB, a SAS/IML software tool for power calculations.
  • To provide power analysis for diverse statistical models, including repeated measures and mixed models.
  • To facilitate the generation of statistical power plots and tables for research publications.

Main Methods:

  • The software implements the "univariate" approach (UNIREP) with Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests.
  • It incorporates "multivariate" approach (MULTIREP) tests: Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda.
  • The tool handles univariate linear models and a range of mixed models with Gaussian errors.

Main Results:

  • POWERLIB offers convenient power calculations for a broad spectrum of multivariate linear and mixed models.
  • Confidence limits for estimated power are provided when using estimated covariance.
  • Output can be directed to a SAS dataset for easy data visualization and reporting.

Conclusions:

  • POWERLIB is a valuable tool for researchers needing power calculations in complex statistical models.
  • The software enhances the statistical rigor of study design and manuscript preparation.
  • It simplifies the process of obtaining and presenting power analysis results.