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I need to interpret this summary. I have a response variable with 5 levels (response) and an explanatory variable (taxon) with 2 levels (raptor and others). Can someone help me?

Call:

multinom(formula = response ~ taxon, data = data, trace = FALSE)

Coefficients:
          (Intercept) taxonraptor
CA         -1.7045477  -0.2410289
Colission  -1.7045071 -12.1472903
E          -0.4519443  -2.1870233
NR         -3.0912802  -8.2838816
OA        -14.3087225  11.6707716
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Difficult to read your results. You need to provide more info about your dependent variable. If you've estimated a multinomial logit model, then you should expect to see 5 parameters:

  • 4 constants which capture the effects of being one level relative to the baseline/reference

  • 1 effect of "taxon" on the level probability

Now it could also be the case that by default "multinom" estimate level-specific effects for "taxon" - In this case you would have four 4 constants + 4 taxon-related effects. But again, your results are difficult to read.

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  • $\begingroup$ As a side note, this model does not seem very interesting. A simple 2-way contingency table would do the job. $\endgroup$
    – Nicolas K
    Feb 7, 2019 at 13:39

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