Hi, I am working on problem 2 of Chapter 8 in Data Analysis and Graphics Using R and don't know how to approach the second half of the question:
In the data set (an artificial one of 3121 patients, that is similar to a subset of the data analyzed in Stiell et al., 2001) head.injury, obtain a logistic regression model relating clinically.important.brain.injury to other variables. Patients whose risk is sufficiently high will be sent for CT (computed tomography). Using a risk threshold of 0.025 (2.5%), turn the result into a decision rule for use of CT. This is what I have so far: > names(head.injury) [1] "age.65" "amnesia.before" [3] "basal.skull.fracture" "GCS.decrease" [5] "GCS.13" "GCS.15.2hours" [7] "high.risk" "loss.of.consciousness" [9] "open.skull.fracture" "vomiting" [11] "clinically.important.brain.injury" > attach(head.injury) > head.glm = glm(clinically.important.brain.injury ~ ., family=binomial, > data=head.injury) > summary(head.glm) Call: glm(formula = clinically.important.brain.injury ~ ., family = binomial, data = head.injury) Deviance Residuals: Min 1Q Median 3Q Max -2.2774 -0.3511 -0.2095 -0.1489 3.0028 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -4.4972 0.1629 -27.611 < 2e-16 *** age.65 1.3734 0.1827 7.518 5.56e-14 *** amnesia.before 0.6893 0.1725 3.996 6.45e-05 *** basal.skull.fracture 1.9620 0.2064 9.504 < 2e-16 *** GCS.decrease -0.2688 0.3680 -0.730 0.465152 GCS.13 1.0613 0.2820 3.764 0.000168 *** GCS.15.2hours 1.9408 0.1663 11.669 < 2e-16 *** high.risk 1.1115 0.1591 6.984 2.86e-12 *** loss.of.consciousness 0.9554 0.1959 4.877 1.08e-06 *** open.skull.fracture 0.6304 0.3151 2.001 0.045424 * vomiting 1.2334 0.1961 6.290 3.17e-10 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 1741.6 on 3120 degrees of freedom Residual deviance: 1201.3 on 3110 degrees of freedom AIC: 1223.3 Number of Fisher Scoring iterations: 6 How do I assess which patients have a high risk level, and how does the risk threshold play into that? Thanks in advance, Diana --------------------------------- [[alternative HTML version deleted]] ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.