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 "R-squared"?
Best wishes Johan
The proportion of deviance explained has been shown to not be such a good measure. You can use the lrm function in the Design package to get various measures including ROC area (C index), Somers' Dxy and Kendall tau rank correlation, Nagelkerke generalization of R-squared for maximum likelihood-based models (related to Maddala and others).
Frank Harrell
y<-cbind(para,unpara) model<-glm(y~log(larvae),binomial) summary(model)
Call: glm(formula = y ~ log(larvae), family = binomial)
Deviance Residuals: Min 1Q Median 3Q Max -2.0633 -1.6218 -0.1871 0.7907 2.7670
Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 1.0025 0.7049 1.422 0.15499 log(larvae) -1.0640 0.3870 -2.749 0.00597 **
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 35.981 on 12 degrees of freedom Residual deviance: 27.298 on 11 degrees of freedom AIC: 40.949
Number of Fisher Scoring iterations: 4
anova(model,test="F")
Analysis of Deviance Table
Model: binomial, link: logit
Response: y
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 12 35.981 log(larvae) 1 8.683 11 27.298 8.6828 0.003212 **
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Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
