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08-13-2009 11:02 AM

Hello,

I have a multinomial ordered response variable (0, 1 and 2) corresponding to population trends (negative, no trend, increasing); 2 continuous independient variables (use and distance) and I am controlling by taxonomy, so I have as random variables family adn genera nested into family. My final model code is:

proc glimmix data=sasuser.Indices_octene ;

class trend family genera;

model trend = use distance distance*distance / dist=multinomial solution;

random family genera(family);

run;

I would like to know:

- Is this a logistic regression with random factors?

- Why can't I get the AIC of the model? (I get it if I delete random factors for the model)

- How could I know if my model is correct? do I have to look at the residuals, and how could I do it?

- Should I wonder about overdispersion? how could I get a measure of that?

Maybe too many questions. Thank you very much.

Grego.

I have a multinomial ordered response variable (0, 1 and 2) corresponding to population trends (negative, no trend, increasing); 2 continuous independient variables (use and distance) and I am controlling by taxonomy, so I have as random variables family adn genera nested into family. My final model code is:

proc glimmix data=sasuser.Indices_octene ;

class trend family genera;

model trend = use distance distance*distance / dist=multinomial solution;

random family genera(family);

run;

I would like to know:

- Is this a logistic regression with random factors?

- Why can't I get the AIC of the model? (I get it if I delete random factors for the model)

- How could I know if my model is correct? do I have to look at the residuals, and how could I do it?

- Should I wonder about overdispersion? how could I get a measure of that?

Maybe too many questions. Thank you very much.

Grego.

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Posted in reply to deleted_user

08-13-2009 11:17 AM

I also found that if I use a normal error distribution, the estimates are almost the same when using multinomial distribution, but with the oposite sign. How should I interpret the sign of the estimates in the model with multinomial error distribution?

Thanks.

Thanks.