Implications of interaction effects on the interpretation of factorial experiments in biology
Factorial experiments are commonly used in biology, particularly to study the way in which two or more factors are related. The presence of a significant interaction indicates that the factors are not independent. In this case, two related aspects should be considered: 1) the post hoc analysis after detecting the significant interaction, and 2) the conclusion on the other hypotheses included in the model. The objective of this work is to discuss the importance and implicances of the significant interactions on the inferences of the hypotheses of factorial models with fixed effects. We include four hypothetical problems in ecology with hypothetical data reflecting different scenarios with significant interactions. In each example, we discuss the possible biological significance of the marginal means of one factor averaged over the levels of the other in the presence of significant interactions, their post hoc analysis, and inferences.
| Main Authors: | , |
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| Format: | Digital revista |
| Language: | spa |
| Published: |
Asociación Argentina de Ecología
2001
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| Online Access: | https://ojs.ecologiaaustral.com.ar/index.php/Ecologia_Austral/article/view/1578 |
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| Summary: | Factorial experiments are commonly used in biology, particularly to study the way in which two or more factors are related. The presence of a significant interaction indicates that the factors are not independent. In this case, two related aspects should be considered: 1) the post hoc analysis after detecting the significant interaction, and 2) the conclusion on the other hypotheses included in the model. The objective of this work is to discuss the importance and implicances of the significant interactions on the inferences of the hypotheses of factorial models with fixed effects. We include four hypothetical problems in ecology with hypothetical data reflecting different scenarios with significant interactions. In each example, we discuss the possible biological significance of the marginal means of one factor averaged over the levels of the other in the presence of significant interactions, their post hoc analysis, and inferences. |
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