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...g linear models. It appears that I need to iterate using GLM, with the weights option and h_i, which I can get from the function hatvalues. For logistic regression, this can be performed by splitting up each observation into response and nonresponse, and using weights as described in Heinze, G. and Schemper, M. (2002), but I'm unsure of how to implement the analogue for log-linear models. A procedure using IWLS is described by Firth (1992) in Dodge and Whittaker (1992), but this book isn't in the local library, and its $141+ on Amazon. I've tried looking at the code in the logistf and brlr...

...58 0.076659442 0.9233405576 150 D 0.0250864459 0.0276820092 0.023163167 0.004518842 0.0205676038 150 U -0.0007676033 -0.0007725071 0.000610456 -0.001382963 0.0006153598 150 Q 0.0258540493 0.0284545164 0.022552711 0.005901805 0.0199522440 150 I also calculated the Schemper and Henderson V measure and obtained v=10.5% I was using the surev package of Lusa Lara; Miceli Rosalba; Mariani LuigiEstimation of predictive accuracy in survival analysis using R and S-PLUS.<http://www.biomedexperts.com/Abstract.bme/17601627/Estimation_of_predictive_accuracy_in_survival_anal...

Dear all, How do I make R show the R-squared (deviance explained by the model) in a logistic regression? Below is how I write my syntax. Basically I want to investigate density-dependence in parasitism of larvae. Note that in the end I perform a F-test because the dispersion factor (residual deviance / residual df) is significantly higher than 1. But how do I make R show the