[R] Cumulative multinomial regression using VGAM

From: Robert Schneider <r_schneid_at_hotmail.com>
Date: Fri, 8 Feb 2008 17:05:58 +0000


I am trying to carry out a multinomial regression using the cumlogit link function. I have tried using the VGAM package, and have gotten some results...

fit1 <- vgam(Y ~ X1 + X2 + X3 + X4,

             data = data1

The problem arrises when I try to get the information out of the fitted object. I can get the coefficient estimates using:


When using the summary, I get the following table:

Number of linear predictors: 5

Names of linear predictors: logit(P[Y<=1]), logit(P[Y<=2]), logit(P[Y<=3]), logit(P[Y<=4]), logit(P[Y<=5])

Dispersion Parameter for cumulative family: 1

Residual Deviance: 618.6155 on 1671 degrees of freedom

Log-likelihood: -309.3078 on 1671 degrees of freedom

Number of Iterations: 11

DF for Terms and Approximate Chi-squares for Nonparametric Effects

              Df Npar Df Npar Chisq P(Chi)

(Intercept):1 1
(Intercept):2 1
(Intercept):3 1
(Intercept):4 1
(Intercept):5 1
X1 1 X2 1 X3 1 X4 1

My question is, how do I get the P values ? I have looked through the structure using str(fit1), but I seem to be unable to find it. I can't find the standard error of the estimates either. Am I missing something ?



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