[R] p-values from VGAM function vglm

[David Winsemius]

On Jun 5, 2009, at 3:15 PM, Steven Matthew Anderson wrote:

> Anyone know how to get p-values for the t-values from the  
> coefficients produced in vglm?
> Attached is the code and output — see comment added to output to  
> show where I need p-values
>
>
> +     print(paste("**********   Using VGAM function gamma2  
> **********"))
> +     modl2<- 
> vglm(MidPoint~Count,gamma2,data=modl.subset,trace=TRUE,crit="c")
> +     print(coef(modl2,matrix=TRUE))
> +     print(summary(modl2))
>
>
> [1] "**********   Using VGAM function gamma2 **********"
> VGLM    linear loop  1 :  coefficients =
> 0.408464609241,  3.255887520104, -0.000220585671
> VGLM    linear loop  2 :  coefficients =
> 2.34723239e-01,  1.28969691e+00, -4.52393778e-05
> VGLM    linear loop  3 :  coefficients =
> 2.19500481e-01,  1.92534895e+00, -3.02160949e-05
> VGLM    linear loop  4 :  coefficients =
> 2.19383151e-01,  2.26845910e+00, -3.00838664e-05
> VGLM    linear loop  5 :  coefficients =
> 2.19383045e-01,  2.34645688e+00, -3.00836087e-05
> VGLM    linear loop  6 :  coefficients =
> 2.19383045e-01,  2.34977070e+00, -3.00836082e-05
> VGLM    linear loop  7 :  coefficients =
> 2.19383045e-01,  2.34977637e+00, -3.00836082e-05
> VGLM    linear loop  8 :  coefficients =
> 2.19383045e-01,  2.34977637e+00, -3.00836082e-05
>                  log(mu) log(shape)
> (Intercept)  2.193830e-01   2.349776
> Count       -3.008361e-05   0.000000
>
> Call:
> vglm(formula = MidPoint ~ Count, family = gamma2, data = modl.subset,
>    trace = TRUE, crit = "c")
>
> Pearson Residuals:
>               Min       1Q   Median      3Q     Max
> log(mu)    -1.7037 -0.82997 0.072275 0.78520 1.72834
> log(shape) -2.5152 -0.32448 0.254698 0.58772 0.70678
>
>
> ######### NEED P-VALUES HERE #########

Perhaps:

dt(summary( modl2 )@coef3[ , 3], 1)


>
>
> Coefficients:
>                    Value Std. Error  t value
> (Intercept):1  2.1938e-01 5.2679e-02  4.16455
> (Intercept):2  2.3498e+00 1.7541e-01 13.39574
> Count         -3.0084e-05 8.9484e-05 -0.33619
>
> Number of linear predictors:  2
>
> Names of linear predictors: log(mu), log(shape)
>
> Dispersion Parameter for gamma2 family:   1
>
> Log-likelihood: -26.39268 on 123 degrees of freedom
>
> Number of Iterations: 8
>
>
> Steven Matthew Anderson
>
> Anderson Research, LLC
> Statistical Programming and Analysis
> SAS (R) Certified Professional
> AdAstra69 at mac.com
-- 
David Winsemius, MD
Heritage Laboratories
West Hartford, CT