Extract Standard Errors of Model Coefficients
These functions extract standard errors of model coefficients from objects returned by modeling functions.
se.coef (object, ...) se.fixef (object) se.ranef (object) ## S4 method for signature 'lm' se.coef(object) ## S4 method for signature 'glm' se.coef(object) ## S4 method for signature 'merMod' se.coef(object)
object |
object of |
... |
other arguments |
se.coef extracts standard errors from objects
returned by modeling functions.
se.fixef extracts standard errors of the fixed effects
from objects returned by lmer and glmer functions.
se.ranef extracts standard errors of the random effects
from objects returned by lmer and glmer functions.
se.coef gives lists of standard errors for coef,
se.fixef gives a vector of standard errors for fixef and
se.ranef gives a list of standard errors for ranef.
Andrew Gelman gelman@stat.columbia.edu; Yu-Sung Su suyusung@tsinghua.edu.cn
Andrew Gelman and Jennifer Hill. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.
# Here's a simple example of a model of the form, y = a + bx + error,
# with 10 observations in each of 10 groups, and with both the
# intercept and the slope varying by group. First we set up the model and data.
group <- rep(1:10, rep(10,10))
mu.a <- 0
sigma.a <- 2
mu.b <- 3
sigma.b <- 4
rho <- 0
Sigma.ab <- array (c(sigma.a^2, rho*sigma.a*sigma.b,
rho*sigma.a*sigma.b, sigma.b^2), c(2,2))
sigma.y <- 1
ab <- mvrnorm (10, c(mu.a,mu.b), Sigma.ab)
a <- ab[,1]
b <- ab[,2]
#
x <- rnorm (100)
y1 <- rnorm (100, a[group] + b[group]*x, sigma.y)
y2 <- rbinom(100, 1, prob=invlogit(a[group] + b*x))
# lm fit
M1 <- lm (y1 ~ x)
se.coef (M1)
# glm fit
M2 <- glm (y2 ~ x)
se.coef (M2)
# lmer fit
M3 <- lmer (y1 ~ x + (1 + x |group))
se.coef (M3)
se.fixef (M3)
se.ranef (M3)
# glmer fit
M4 <- glmer (y2 ~ 1 + (0 + x |group), family=binomial(link="logit"))
se.coef (M4)
se.fixef (M4)
se.ranef (M4)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.