dear List: glm(a~b+c,family=binomial,data=x)->fit deviance(fit) returns the same as the residual deviance.
I don't not know much about logistic regression.Some book tells that: " Deviance (likelihood ratio statistic): Deviance = -2log( likelihoodof the currentmodel /likelihoodof thesaturated model) Note: (1). The current model is the model of interest. (2). The saturated model is the full model that considers observed data as parameters, thus there are as many parameters as data points (the full model gives a perfect fit to the data). Under this model, the maximum of the likelihood is achieved as much as we can. (3). If the current model is a good model, the ratio in the bracket will be close to 1. Otherwise, the ratio will be small. (4). Therefore, large D suggests the current model is a poor description of the data. (5). The deviance for logistic regression plays the same role as the residual sum of squares in linear regression. " Is the residual deviance in fact the Deviance mentioned in that book? A got a deviance about 2000, which looks in no sense simila to that of the residual sum of squares in linear regression. Thank you very much in advance! -- View this message in context: http://www.nabble.com/How-to-extract-the-Deviance--of-a-glm-fit-result-tf4848589.html#a13872589 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
