?str
It's a pretty fundamental function for understanding R objects.
> str(summary(vglm.D93))
Formal class 'summary.vglm' [package "VGAM"] with 43 slots
..@ coef3 : num [1:5, 1:3] 3.04 -4.54e-01 -2.93e-01
1.00e-15 9.33e-16 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:5] "(Intercept)" "outcome2" "outcome3"
"treatment2" ...
.. .. ..$ : chr [1:3] "Value" "Std. Error" "t value"
..@ cov.unscaled : num [1:5, 1:5] 0.0292 -0.0159 -0.0159 -0.02
-0.02 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:5] "(Intercept)" "outcome2" "outcome3"
"treatment2" ...
.. .. ..$ : chr [1:5] "(Intercept)" "outcome2" "outcome3"
"treatment2" ...
<snipped about three pages of further output>
On Jun 5, 2009, at 7:28 PM, Steven Matthew Anderson wrote:
Thank you for your reply. Related question ... how do you know the
matrix of values in the summary(modl2) was called coef3? Is there a
function for extracting that information?
dt(summary( modl2 )@coef3[ , 3], 1)
Thank you,
Steve
On Jun 5, 2009, at 2:18 PM, David Winsemius wrote:
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
adastr...@mac.com
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
Steven Matthew Anderson
Anderson Research, LLC
Statistical Programming and Analysis
SAS (R) Certified Professional
adastr...@mac.com
Ad Astra per Aspera
שָׁלוֹם
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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