There are many different ways to identify which factors or combination of factors in your design are having an effect on your data. Some of these methods are more automated and handled as a part of the model fitting process.
Here you will be shown a method that first identifies significant effects, from which you can visualise plots and assess before deciding which you want to build a model from.
Before knowing how to identify them it’s probably best to start with what effects are.
Learn what statistical tests are used and how effects are identified as significant.
Synthace makes the process of finding and assessing significant effects easy, follow the steps here to learn how.
Just because the statistics says there is a p-value implying significance, doesn’t mean you should include the effect. Apply your biological knowledge and learn how to manually include or remove effects to be modelled.
Any effects that have been identified as significant or ones that have been added manually can be assessed visually with a helpful set of interactive plots that can help you understand when to remove or add an effect that is maybe sat on the line of significance.
How to create a model from significant effects (Coming Soon!)
Once you have identified a set of effects that you believe are significant or look interesting, use them to build and fit a model to your data. This article explains how to do this, step by step.