The Fit Two Level Screening platform is a modeling platform that you can use to analyze experimental data that results from a screening design. The Fit Two Level Screening platform helps you select a model by identifying effects that have a large impact on the response.

The Fit Two Level Screening platform is based on the principle of effect sparsity (Box and Meyer, 1986). This principle asserts that relatively few of the effects that you study in a screening design are active. Most are inactive, meaning that their true effects are zero and that their estimates are random error.

A screening design often provides no degrees of freedom for error. Consequently, classical tests for effects are not available. In such cases, the Fit Two Level Screening platform is particularly useful.