| plot.swgee {swgee} | R Documentation |
plot.swgee
Description
Produce the plot of the quadratic extrapolation curve for any covariables with measurement error in the swgee model
Usage
## S3 method for class 'swgee'
## S3 method for class 'swgee'
plot(x, covariate, ...)
Arguments
x |
object of class 'swgee' |
covariate |
covariates specified in the formula |
... |
further arguments passed to or from other functions. |
Value
Plot the simulation and extrapolation step
Author(s)
Juan Xiong<jxiong@szu.edu.cn>, Grace Y. Yi<yyi@uwaterloo.ca>
References
Cook, J.R. and Stefanski, L.A. (1994) Simulation-extrapolation estimation in parametric measurement error models. Journal of the American Statistical Association, 89, 1314-1328.
Carrol, R.J., Ruppert, D., Stefanski, L.A. and Crainiceanu, C. (2006) Measurement error in nonlinear models: A modern perspective., Second Edition. London: Chapman and Hall.
Yi, G. Y. (2008) A simulation-based marginal method for longitudinal data with dropout and mismeasured covariates. Biostatistics, 9, 501-512.
Examples
require(gee)
require(mvtnorm)
data(BMI)
bmidata <- BMI
rho <- 0
sigma1 <- 0.5
sigma2 <- 0.5
sigma <- matrix(0,2,2)
sigma[1,1] <- sigma1*sigma1
sigma[1,2] <- rho*sigma1*sigma2
sigma[2,1] <- sigma[1,2]
sigma[2,2] <- sigma2*sigma2
set.seed(1000)
##swgee method ##########
output2 <- swgee(bbmi~sbp+chol+age, data = bmidata, id = id,
family = binomial(link="logit"),corstr = "independence",
missingmodel = O~bbmi+sbp+chol+age, SIMEXvariable = c("sbp","chol"),
SIMEX.err = sigma, repeated = FALSE, B = 20, lambda = seq(0, 2, 0.5))
summary(output2)
plot(output2,"sbp")