print.summary.BImm: Print a summary.BImm class model.

Description Usage Arguments Value Author(s) References See Also Examples

Description

print.summary.BImm is the summary.BImm specific method fot the generic function print which prints objects returned by modelling functions.

Usage

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## S3 method for class 'summary.BImm'
print(x, ...)

Arguments

x

a summary.BImm class model.

...

for extra arguments.

Value

Prints a summary.BImm object.

Author(s)

J. Najera-Zuloaga

D.-J. Lee

I. Arostegui

References

Breslow N. E. & Calyton D. G. (1993): Approximate Inference in Generalized Linear Mixed Models, Journal of the American Statistical Association, 88, 9-25

McCulloch C. E. & Searle S. R. (2001): Generalized, Linear, and Mixed Models, Jhon Wiley & Sons

Pawitan Y. (2001): In All Likelihood: Statistical Modelling and Inference Using Likelihood, Oxford University Press

See Also

BImm, summary.BImm

Examples

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set.seed(5)
# Fixing parameters for the simulation:
nObs <- 1000
m <- 10
beta <- c(1.5,-1.1)
sigma <- 0.8

# Simulating the covariate:
x <- runif(nObs,-5,5)

# Simulating the random effects:
z <- as.factor(rBI(nObs,5,0.5,2))
u <- rnorm(6,0,sigma)

# Getting the linear predictor and probability parameter.
X <- model.matrix(~x)
Z <- model.matrix(~z-1)
eta <- beta[1]+beta[2]*x+crossprod(t(Z),u)
p <- 1/(1+exp(-eta))

# Simulating the response variable
y <- rBI(nObs,m,p)

# Apply the model
model <- BImm(fixed.formula = y~x,random.formula = ~z,m=m)
sum.model <- summary(model)
print(sum.model) # or just sum.model

HRQoL documentation built on May 2, 2019, 5:42 a.m.