You have performed a complex experiment generating a lot of data and the next step is to try and understand what it all means. A step towards that is identifying of all the different factors that you were investigating which ones or combination of them influence the signal in your data.
In the following documents you will learn different techniques for how to identify which of your factors or factor interactions, otherwise known as effects, are significant and should be used to build and fit a model.
Background document explaining what effects are and the different ways to identify them and include them in your model.
Subsection describing the Find Effects tab, how it works and how to use it.
Subsection describing the stepwise regression technique for automated model building, how it works and how to use it.
Subsection describing the LASSO regression technique for automated model building, how it works and how to use it.
Background document explaining what blocking factors are, why they can be important to include in your analysis, and how they impact the calculated statistics.
Selecting effects manually (Coming Soon!)
Instructional document explaining how to use manual selection to define or edit your model.