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How do you find nested factors?
A factor B is nested in factor A if each level of B occurs in conjunction with only one level of A. (In other words, if there is a completely different set of levels of B for every level of A.) Recall: Two factors A and B are crossed if every level of A occurs with every level of B.
What are crossed and nested factors?
If two factors are crossed, you can calculate an interaction. If they are nested, you cannot because you do not have every combination of one factor along with every combination of the other.
How are nested random effects different from crossed random effects?
Nested random effects occur when a lower level factor appears only within a particular level of an upper level factor. For example, pupils within classes at a fixed point in time. Crossed random effects means that a given factor appears in more than one level of the upper level factor.
Can you do cross tabulation of nested factors?
If they are nested, you cannot because you do not have every combination of one factor along with every combination of the other. If you’re not sure whether two factors in your design are crossed or nested, the easiest way to tell is to run a cross tabulation of those factors. Here is an example.
What’s the difference between nested factors and crossed factors?
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.
When do nested random effects occur in lme4?
Nested random effects occur when a lower level factor appears only within a particular level of an upper level factor. For example, pupils within classes at a fixed point in time. In lme4 I thought that we represent the random effects for nested data in either of two equivalent ways: (1|class/pupil) # or (1|class) + (1|class:pupil)