I maintain the Devore5 package for R. This package provides the data sets from Jay Devore's text "Probability and Statistics for Engineering and the Sciences (5th ed)". I am having difficulty reproducing some logistic regression results from the textbook. Perhaps this is because I am not using the glm function correctly. The data from Example 13.5 (page 559 for those with a copy of the book) are "the launch temperatures and the incidence of failure for O-rings in 24 space shuttle launches prior to the Challenger disaster of January 1986." Here are the data (Temperature in degrees Fahrenheit).
library(Devore5) data(xmp13.05) xmp13.05
Temperature Failure 1 53 Y 2 56 Y 3 57 Y 4 63 N 5 66 N 6 67 N 7 67 N 8 67 N 9 68 N 10 69 N 11 70 N 12 70 Y 13 70 N 14 70 Y 15 72 N 16 73 N 17 75 N 18 75 Y 19 76 N 20 76 N 21 78 N 22 79 N 23 80 N 24 81 N
summary(xmp13.05)
Temperature Failure
Min. :53.00 N:18
1st Qu.:67.00 Y: 6
Median :70.00
Mean :69.92
3rd Qu.:75.25
Max. :81.00
Devore shows the parameter estimates for a logistic regression model
fit by JMP as
Term Estimate Std Error ChiSquare Prob>ChiSq
Intercept 10.8753321 5.7031291 3.64 0.0565
temp -0.1713202 0.0834419 4.22 0.0401
I have not been able to reproduce these results in R. My results are
> fm1 <- glm(Failure ~ Temperature, data = xmp13.05, family = "binomial")
> summary(fm1)
Call:
glm(formula = Failure ~ Temperature, family = "binomial", data = xmp13.05)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.12489 -0.72335 -0.40139 -0.04056 2.22441
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 11.74641 6.01916 1.952 0.0510 .
Temperature -0.18843 0.08906 -2.116 0.0344 *
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 26.992 on 23 degrees of freedom
Residual deviance: 20.482 on 22 degrees of freedom
AIC: 24.482
Number of Fisher Scoring iterations: 4
Am I doing something wrong?
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