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Published in Agron. J. 96:1323-1330 (2004).
© American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA

Statistics

Simultaneous Tests and Confidence Intervals for the Evaluation of Agricultural Field Trials

Cornelia Frömke* and Frank Bretz

Research Unit of Bioinformatics, Univ. of Hannover, Herrenhaeuser Strasse 2, 30419 Hannover, Germany

* Corresponding author (froemke{at}bioinf.uni-hannover.de)

Received for publication June 18, 2003. Agricultural designs commonly involve the simultaneous analysis of more than two factors and more than two levels for each factor. This article addresses the use of adequate statistical tests while taking multiplicity into account. Two data sets and their appropriate statistical analysis are presented as illustrative examples. The first data set is a split-plot design, with two fixed factors and a random block factor, and the second data set is a two-factor factorial complete randomized design. Two SAS macros are presented to analyze the data sets properly in terms of the multiplicity problem, and these macros compute simultaneous confidence intervals and multiplicity-adjusted p values. The two macros, called %SimultanTests and %SimultanIntervals, are based on exact evaluations of the underlying multivariate t distribution and are extensions of the published macros %SimTests and %SimIntervals. The macros are widely applicable tools, which can be used with relatively little effort for the analysis of many agricultural designs.

Abbreviations: MCT, multiple-contrast test • SCT, single-contrast test






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