Noticed variables usually tend to be correlated, Whilst manipulated kinds usually tend to be unbiased. Over and above that, there is not any change in how SPSS estimates a manipulated or observed variable.
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I've discovered that another excuse to utilize the marginal suggests is When you've got unequal cell measurements. I've performed a two-way anova for example wherein the groups aren’t the exact same size.
– But what if I've a measured aspect, which I tend not to treat like a covariate, but being an unbiased variable?
Even though that difference could also look within the regression coefficients, looking at the indicates by themselves give you a context and makes interpretation far more easy. This is certainly especially true When you've got interactions in the model.
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