arm (version 1.1-14)

sim: Functions to Get Posterior Distributions

Description

This generic function gets posterior simulations of sigma and beta from a lm object, or simulations of beta from a glm object, or simulations of beta from a mer object

Usage

sim(object, ...)

## S3 method for class 'lm':
sim(object, n.sims = 100)
## S3 method for class 'glm':
sim(object, n.sims = 100)
## S3 method for class 'mer':
sim(object, n.sims = 100)

Arguments

object

the output of a call to "lm" with n data points and k predictors.

...

further arguments passed to or from other methods.

n.sims

number of independent simulation draws to create.

Value

• sigma.sim
  vector of n.sims random draws of sigma (for glm's, this just returns a vector of 1's or else of the square root of the overdispersion parameter if that is in the model)
• beta.sim
  matrix (dimensions n.sims x k) of n.sims random draws of beta

References

Andrew Gelman and Jennifer Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2006.

See Also

display, lm, glm, lmer

Examples

#Examples of "sim" 
 set.seed (1)
 J <- 15
 n <- J*(J+1)/2
 group <- rep (1:J, 1:J)
 mu.a <- 5
 sigma.a <- 2
 a <- rnorm (J, mu.a, sigma.a)
 b <- -3
 x <- rnorm (n, 2, 1)
 sigma.y <- 6
 y <- rnorm (n, a[group] + b*x, sigma.y)
 u <- runif (J, 0, 3)
 y123.dat <- cbind (y, x, group)
# Linear regression 
 x1 <- y123.dat[,2]
 y1 <- y123.dat[,1]
 M1 <- lm (y1 ~ x1)
 display(M1)
 M1.sim <- sim(M1)
 
# Logistic regression 
 u.data <- cbind (1:J, u)
 dimnames(u.data)[[2]] <- c("group", "u")
 u.dat <- as.data.frame (u.data)
 y <- rbinom (n, 1, invlogit (a[group] + b*x))
 M2 <- glm (y ~ x, family=binomial(link="logit"))
 display(M2)
 M2.sim <- sim (M2)

# Using lmer:
# Example 1
 E1 <- lmer (y ~ x + (1 | group))
 display(E1)
 E1.sim <- sim (E1)

# Example 2
 u.full <- u[group]
 E2 <- lmer (y ~ x + u.full + (1 | group))
 display(E2)
 E2.sim <- sim (E2)

# Example 3 
 y <- rbinom (n, 1, invlogit (a[group] + b*x))
 E3 <- glmer (y ~ x + (1 | group), family=binomial(link="logit"))
 display(E3)
 E3.sim <- sim (E3)