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Compare goodness of fit between models

2 messages · Sverre Stausland, David Duffy

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Dear mixed-models helpers,

say I have a study where I try to predict people's response to how
happy they are on a 1-5 scale. The data frame has the dependent
variable "Response" (1-5) and a random effect for "Subject". I fit a
model with the fixed effects "Height" and "Income". I also fit a model
with the fixed effects "Weight" and "Hours of sleep". In this case
where the dependent variable, subjects, and the number of observations
are the same in the two models, am I justified to directly compare the
goodness-of-fit values for the two models?

Please note that this is a hypothetical example. I know that I in this
case should just fit a model with all four fixed effects. In the real
case I have, that is not an option.

Thanks
Sverre
1 day later
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On Wed, 20 Jul 2011, Sverre Stausland wrote:

            
You can, but you can't draw any substantive conclusions ;)  If A and B are 
equally important independent causes of Y, then I might expect Y~A and Y~B 
submodels to have equal goodness-of-fit values.  If A causes B, ditto.
In a graphical or SEM framework, you are able to incorporate external 
information about Weight and Height into your model.

Just 2c, David.