Methods for extracting information from fitted simplex regression model
objects of class
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fitted model object of class "simplexreg"
character specifying type of residuals to be included, see
currently not used
These functions make it possible to extract information from objects of class
"simplexreg". Wald statistics as well as the p-values of regression coefficients
are given in the
summary output. If
GEE = FALSE, based on the fitted
coefficients, a χ^2 test is performed and the p-value is reported in the output.
Otherwise, coefficients of the autocorrelation α, ρ, (see Song
et. al (2004)), are also involved.
Model coefficients and their covariance matrix could be extracted by the
vcov, respectively. For simplex GLM models (
GEE = FALSE), Akaike Information
Criterion and Bayesian Information Criterion could be calculated using generic functions
Barndorff-Nielsen, O.E. and Jorgensen, B. (1991) Some parametric models on the simplex. Journal of Multivariate Analysis, 39: 106–116
Jorgensen, B. (1997) The Theory of Dispersion Models. London: Chapman and Hall
Song, P. and Qiu, Z. and Tan, M. (2004) Modelling Heterogeneous Dispersion in Marginal Models for Longitudinal Proportional Data. Biometrical Journal, 46: 540–553
Zhang, P. and Qiu, Z. and Shi, C. (2016) simplexreg: An R Package for Regression Analysis of Proportional Data Using the Simplex Distribution. Journal of Statistical Software, 71: 1–21
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## fit the model data("sdac", package = "simplexreg") sim.glm2 <- simplexreg(rcd~ageadj+chemo|age, link = "logit", data = sdac) data("retinal", package = "simplexreg") sim.gee2 <- simplexreg(Gas~LogT+LogT2+Level|LogT+Level|Time, link = "logit", corr = "AR1", id = ID, data = retinal) ## extract information summary(sim.glm2, type = "appstdPerr") coef(sim.glm2) vcov(sim.glm2) AIC(sim.glm2) BIC(sim.glm2) summary(sim.gee2, type = "stdscor") coef(sim.gee2) vcov(sim.glm2)
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