Crossed factors

Member Training: Elements of Experimental Design

Whether or not you run experiments, there are elements of experimental design that affect how you need to analyze many types of studies.

The most fundamental of these are replication, randomization, and blocking. These key design elements come up in studies under all sorts of names: trials, replicates, multi-level nesting, repeated measures. Any data set that requires mixed or multilevel models has some of these design elements. [Read more…] about Member Training: Elements of Experimental Design

Member Training: Crossed and Nested Factors

by Karen Grace-Martin Leave a Comment

We often talk about nested factors in mixed models — students nested in classes, observations nested within subject.

But in all but the simplest designs, it’s not that straightforward. [Read more…] about Member Training: Crossed and Nested Factors

The Difference Between Crossed and Nested Factors

by Karen Grace-Martin 17 Comments

One of those tricky, but necessary, concepts in statistics is the difference between crossed and nested factors.

As a reminder, a factor is any categorical independent variable. In experiments, or any randomized designs, these factors are often manipulated. Experimental manipulations (like Treatment vs. Control) are factors.

Observational categorical predictors, such as gender, time point, poverty status, etc., are also factors. Whether the factor is observational or manipulated won’t affect the analysis, but it will affect the conclusions you draw from the results.