[R] generate random number

[Dimitris Rizopoulos]

check the following code:

# settings
n <- 100 # number of sample units
p <- 10 # number of repeated measurements
N <- n * p # total number of measurements
t.max <- 3

# parameter values
betas <- c(0.5, 0.4, -0.5, -0.8) # fixed effects (check also 'X' below)
sigma.b <- 2 # random effects variance

# id, treatment & time
id <- rep(1:n, each = p)
treat <- rep(0:1, each = n/2)
time <- seq(0, t.max, length.out = p)

# simulate random effects
b <- rnorm(n, sd = sigma.b)

# simulate longitudinal process conditionally on random effects
time.rep <- rep(time, n)
treat.rep <- rep(treat, each = p)
X <- cbind(1, treat.rep,
     time.rep, treat.rep * time.rep) # fixed effects design matrix
muY <- plogis(c(X %*% betas) + b[id]) # conditional probabilities
y <- rbinom(N, 1, muY) # simulate binary responses

# put the simulated data in a data.frame
simulData <- data.frame(
     id = id,
     y = y,
     treat = treat.rep,
     time = time.rep
)

# fit the model
library(glmmML)
fit <- glmmML(y ~ treat * time, data = simulData, cluster = id)
summary(fit)


I hope it helps.

Best,
Dimitris


Odette Gaston wrote:
> Hi everybody,
> 
> I am currently working on glmmML() and wish to generate random number to do
> some tests, however, glmm was hypothesized the mixed distributions with
> normal  and binomial in terms of having a random effect. How would you be
> able to generate random number in this case? Is there a function in R to
> generate random number of  mixed distribution (normal+binomial)? Any
> comments would be appreciated.
> 
> Many thanks,
> Odette
> 
> 	[[alternative HTML version deleted]]
> 
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-- 
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus Medical Center

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