Neither kind of means are right or wrong - they answer different questions. (This can be viewed from a regression/general linear model perspective, with categorical factors being dummy coded). In an imbalanced factorial anova design, the factors are essentially confounded "covariates" and the LSmeans are adjusting for that, giving you an average of cell averages, rather than just the marginal means blind to (and confounded with the other factor(s)). Yes, SAS's "LSMeans" are means adjusted for the covariate(s).
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