compCoef function

Compare Regression Coefficiente between Nested Models

Comparing regression coefficients between models when one model is nested within another for clustered data.

compCoef(fit0, fit1)

Arguments

• fit0: a fitted object of class geese
• fit1: another fitted object of class geese

Returns

a list of two components: - delta: estimated difference in the coefficients of common covariates from fit0 and fit1 - variance: estimated variance matrix of delta

Examples

## generate clustered data
gendat <- function(ncl, clsz) {
## ncl: number of clusters
## clsz: cluster size (all equal)
  id <- rep(1:ncl, each = clsz)
  visit <- rep(1:clsz, ncl)
  n <- ncl * clsz
  x1 <- rbinom(n, 1, 0.5) ## within cluster varying binary covariate
  x2 <- runif(n, 0, 1)   ## within cluster varying continuous covariate
  ## the true correlation coefficient rho for an ar(1)
  ## correlation structure is 2/3
  rho <- 2/3
  rhomat <- rho ^ outer(1:4, 1:4, function(x, y) abs(x - y))
  chol.u <- chol(rhomat)
  noise <- as.vector(sapply(1:ncl, function(x) chol.u %*% rnorm(clsz)))
  y <- 1 + 3 * x1 - 2 * x2 + noise
  dat <- data.frame(y, id, visit, x1, x2)
  dat
}

simdat <- gendat(100, 4)
fit0 <- geese(y ~ x1, id = id, data = simdat, corstr = "un")
fit1 <- geese(y ~ x1 + x2, id = id, data = simdat, corstr = "un")
compCoef(fit0, fit1)

References

Allison, P. D. (1995). The impact of random predictors on comparisons of coefficients between models: Comment on Clogg, Petkova, and Haritou. American Journal of Sociology, 100 (5), 1294--1305.

Clogg, C. C., Petkova, E., and Haritou, A. (1995). Statistical methods for comparing regression coefficients between models. American Journal of Sociology, 100 (5), 1261--1293.

Yan, J., Aseltine, R., and Harel, O. (2011). Comparing Regression Coefficients Between Nested Linear Models for Clustered Data with Generalized Estimating Equations. Journal of Educational and Behaviorial Statistics, Forthcoming.

Author(s)

Jun Yan jyan.stat@gmail.com