I'm currently studying experiments where one or more factors are random, i.e. random effects models. In this model a professor explained that the Expected Mean Square calculations for any factor are:(adsbygoogle = window.adsbygoogle || []).push({});

Expected Mean Square (factor) = (lower level error terms) + (term relating to factor)

For example, if A and B are both random, then

Expected Mean Square (A) = (Error variance) + n*(AB Interaction variance) + n*b*(A variance)

My question is why does the AB interaction variance get classified as a 'lower level' error in relation to A and as a result get included in the Expected Mean Square calculation for factor A?

Thanks.

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# 'Low Level' Error Terms in Expected Mean Square Calculation

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