"Note that in cases such as these, where $A{B1}$ vs. $A{B2}$ are nested within levels of $B$, it is necessary to include the effect of $B$ (part of speech) in the model, even if one is only interested in the effect of $A$ (word frequency) within levels of $B$ (part of speech). Leaving out factor $B$ in this case can lead to biases in parameter estimation in the case the data are not fully balanced."
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"Note that in cases such as these, where $A{B1}$ vs. $A{B2}$ are nested within levels of $B$, it is necessary to include the effect of $B$ (part of speech) in the model, even if one is only interested in the effect of $A$ (word frequency) within levels of $B$ (part of speech). Leaving out factor $B$ in this case can lead to biases in parameter estimation in the case the data are not fully balanced."