[R] gamlss() vs glm() standard errors via summary() vs vcov()

[1/k^c]

Thank you, Peter!

Sincerely,
KeithC.

On Wed, Jul 4, 2018 at 4:11 AM, Peter Dalgaard <pdalgd using gmail.com> wrote:
>> # Extract SEs via vcov()
>> SEvcov1<-exp(coef(fit1)) *sqrt(diag(vcov(fit1)))
>> SEvcov2<-exp(coef(fit2))*sqrt(diag(vcov(fit2)))
>
> What makes you think that you need to multiply with exp(coef(....)) here???
>
> -pd
>
>> On 4 Jul 2018, at 11:08 , 1/k^c <kchamberln using gmail.com> wrote:
>>
>> Hi R-helpers,
>>
>> I was working with some count data using gamlss() and glm(), and
>> noticed that the standard errors from the two functions correspond
>> when extracting from either the model summary for both functions, or
>> using vcov for both functions, but the standard errors between those
>> methods do not correspond. I have been lead to believe that in SAS and
>> Stata, the SEs do correspond between the different methods. Can anyone
>> assist me in understanding what's different between the two types of
>> SEs I seem to be encountering when using R with either glm or gamlss?
>> I feel like I'm missing something obvious. I have included a small
>> reproducible example below.
>>
>> library(COUNT) # for myTable()
>> library(gamlss)
>> len<-50
>> seeder<-250
>> set.seed(seeder)  # reproducible example
>> dat<-rpois(c(1:len), lambda=2)
>> myTable(dat)
>> fac<-gl(n=2, k=1, length=len, labels = c("control","treat"))
>>
>> # Fit gamlss() and glm() models
>> fit1<-gamlss(dat~fac, family="PO")
>> fit2<-glm(dat~fac, family="poisson")
>>
>> # Extract SEs from model summaries
>> SESum1<-summary(fit1)[,"Std. Error"]
>> SESum2<-coef(summary(fit2))[,"Std. Error"]
>> cbind(SESum1, SESum2) # Corresponds
>>
>> # Extract SEs via vcov()
>> SEvcov1<-exp(coef(fit1)) *sqrt(diag(vcov(fit1)))
>> SEvcov2<-exp(coef(fit2))*sqrt(diag(vcov(fit2)))
>> cbind(SEvcov1, SEvcov2) # Corresponds
>>
>> # Compare between summary() and vcov() extraction. Missmatch.
>> cbind(SESum1, SEvcov1)
>>
>> ______________________________________________
>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> --
> Peter Dalgaard, Professor,
> Center for Statistics, Copenhagen Business School
> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
> Phone: (+45)38153501
> Office: A 4.23
> Email: pd.mes using cbs.dk  Priv: PDalgd using gmail.com
>
>
>
>
>
>
>
>
>