Maja,
The need to interpret parameters in log-linear models (and therefore,
the need to understand how the model is parameterized) often vanishes
if you visualize the fitted model or the residuals in a mosaic display.
e.g., ucb1 asserts Admit is jointly independent of Gender and Dept ---
fits
On Wed, 18 Feb 2009, maiya wrote:
I realise that in the case of loglin the parameters are clacluated post
festum from the cell frequencies,
however other programmes that use Newton-Raphson as opposed to IPF work the
other way round, right?
In which case one would expect the output of
I am fairly new to log-linear modelling, so as opposed to trying to fit
modells, I am still trying to figure out how it actually works - hence I am
looking at the interpretation of parameters. Now it seems most people skip
this part and go directly to measuring model fit, so I am finding very few
On Wed, 18 Feb 2009, maiya wrote:
I am fairly new to log-linear modelling, so as opposed to trying to fit
modells, I am still trying to figure out how it actually works - hence I am
looking at the interpretation of parameters. Now it seems most people skip
this part and go directly to
I realise that in the case of loglin the parameters are clacluated post
festum from the cell frequencies,
however other programmes that use Newton-Raphson as opposed to IPF work the
other way round, right?
In which case one would expect the output of parameters to be limited to the
particular
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