Exercise 1.21 concerned a study comparing forced expiratory volume (y =

fev1 in the data file FEV.dat at the text website) for three drugs, adjusting for a baseline measurement. For the R output shown, using notation you define, state the model that was fitted, and interpret all results shown.

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> summary(lm(fev1 ~ base + factor(drug)))

Estimate Std. Error

(Intercept) 1.1139 0.2999 base 0.8900 0.1063 factor(drug)b 0.2181 0.1375 factor(drug)p -0.6448 0.1376

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Residual standard error: 0.4764 on 68 degrees of freedom Multiple R-squared: 0.6266, Adjusted R-squared: 0.6101

> anova(lm(fev1 ~ base + factor(drug)))

Analysis of Variance Table Df Sum Sq Mean Sq base 1 16.2343 16.2343 factor(drug) 2 9.6629 4.8315 Residuals 68 15.4323 0.2269

> quantile(rstandard(lm(fev1 ~ base + factor(drug))))

0% 25% 50% 75% 100%

-2.0139 -0.7312 -0.1870 0.6341 2.4772

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