Dear All, I have two questions regarding the use of the R2BayesX package for Bayesian analysis. First, is it possible to generate predictions based on the fitted model? According to Gelman and Hill (2007, pp. 361-363), there are at least two ways to do this in BUGS: (1) generate additional data points with the dependent variable coded as missing (and all the independent variables fixed at desirable levels) and let BUGS fill in the values; (2) use R to combine the estimated BUGS results and data value to get the new predictions. Can these be done with R2BayesX? Can someone offer some examples?
Second, I wonder whether R2BayesX can estimate grouped logistic regression models. One example is the Surgical example in the BUGS example collection ( http://mathstat.helsinki.fi/openbugs/Examples/Surgical.html) where the dependent variable consists (1) the number of deaths and (2) the number of total patients. Many thanks for the help. Best, Shige Reference Gelman, A., and J. Hill. 2007. *Data analysis using regression and multilevel/hierarchical models*. Cambridge, England: Cambridge University Press New York. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
