Abstract
In a two-way cross-classified experiment, one is almost always interested in whether the two factors interact or not. When there are no independent replications, there are no traditional tests for interaction. This research considers the problem of analyzing a two-way cross-classified experiment using multiplicative interaction models when there are no independent replications and interaction between the two factors may exist. The purpose of this research is to develop SAS® macros to provide user-friendly statistical software for the analysis of interaction in two-way experiments. The macros also provide many useful graphical displays including displays to help one determine the pattern of interaction when a pattern exists and to help one interpret the results of the analyses.
Keywords
Two-Way experiments, AMMI, Genotype-by-Environmental interaction
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Lee, Eun-Joo and Johnson, Dallas E.
(2004).
"STATISTICAL ANALYSIS SOFTWARE FOR MULTIPLICATIVE INTERACTION MODELS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1156
STATISTICAL ANALYSIS SOFTWARE FOR MULTIPLICATIVE INTERACTION MODELS
In a two-way cross-classified experiment, one is almost always interested in whether the two factors interact or not. When there are no independent replications, there are no traditional tests for interaction. This research considers the problem of analyzing a two-way cross-classified experiment using multiplicative interaction models when there are no independent replications and interaction between the two factors may exist. The purpose of this research is to develop SAS® macros to provide user-friendly statistical software for the analysis of interaction in two-way experiments. The macros also provide many useful graphical displays including displays to help one determine the pattern of interaction when a pattern exists and to help one interpret the results of the analyses.
