21 Bootstrapping Regression Models - SAGE Publications …

21 BootstrappingRegressionModelsBootstrappi ngis a nonparametric approach to statistical inference that substitutes computationfor more traditional distributional assumptions and asymptotic offersa number of advantages: The bootstrap is quite general, although there are some cases in which it fails. Because it does not require distributional assumptions (such as normally distributed errors),the bootstrap can provide more accurate inferences when the data are not well behaved orwhen the sample size is small. It is possible to apply the bootstrap to statistics with sampling distributions that are difficultto derive, even asymptotically.

588 Chapter 21. Bootstrapping Regression Models Table 21.1 Contrived “Sample” of Four Married Couples, Showing Husbands’ and Wives’ Incomes in Thousands of Dollars Observation Husband’s Income Wife’s Income Difference Yi 124 18 6 214 17−3 340 35 5 444 41 3 where z.025 = 1.96 is the standard normal value with a probability of .025 ...

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