# Compare Regression Coefficiente between Nested Models Comparing regression coefficients between models when one model is nested within another for clustered data. ```r 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 ```r ## 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

compCoef function