I did a glm
and I just want to extract the standard errors of each coefficient. I saw on the internet the function se.coef()
but it doesn't work, it returns "Error: could not find function "se.coef""
.
Extract standard errors from glm [duplicate]
Asked Answered
Might help to put up some data and example code. –
Trooper
The information you're after is stored in the coefficients
object returned by summary()
. You can extract it thusly: summary(glm.D93)$coefficients[, 2]
#Example from ?glm
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
print(d.AD <- data.frame(treatment, outcome, counts))
glm.D93 <- glm(counts ~ outcome + treatment, family=poisson())
#coefficients has the data of interest
> summary(glm.D93)$coefficients
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.044522e+00 0.1708987 1.781478e+01 5.426767e-71
outcome2 -4.542553e-01 0.2021708 -2.246889e+00 2.464711e-02
outcome3 -2.929871e-01 0.1927423 -1.520097e+00 1.284865e-01
treatment2 1.337909e-15 0.2000000 6.689547e-15 1.000000e+00
treatment3 1.421085e-15 0.2000000 7.105427e-15 1.000000e+00
#So extract the second column
> summary(glm.D93)$coefficients[, 2]
(Intercept) outcome2 outcome3 treatment2 treatment3
0.1708987 0.2021708 0.1927423 0.2000000 0.2000000
Take a look at names(summary(glm.D93))
for a quick review of everything that is returned. More details can be found by checking out summary.glm
if you want to see the specific calculations that are going on, though that level of detail probably is not needed every time, unless you <3 statistics.
Are the standard errors stored within the
glm.D93
object? I couldn't eyeball it using str()
. Or does summary()
explicitly calculate the errors? –
Allin @Allin - AFAIK they are calculated directly by
summary.glm
. If you type the function into your console sans ()
and then scroll down about 25 lines, you'll see where it's calculated. –
Overindulge Another way:
sqrt(diag(vcov(glm.D93)))
This is beautiful - pure and simple. –
Snowshed
se.coef() actually does work. But it's not in the base package: it's in the {arm} package: http://www.inside-r.org/packages/cran/arm/docs/se.ranef
© 2022 - 2024 — McMap. All rights reserved.