In Chapter 3 we demonstrated that the two-sample test was more powerful than the traditional test when the errors were not normally distributed. In this chapter we consider a test for a subset of coefficients in a regression model. Will the performance that we saw with two-sample tests carry over to the tests that are used with more complex models?
An adaptive test for a subset of coefficients in a linear regression model will be used for all tests in this chapter and the next three chapters. The adaptive test, which is a generalization of the two-sample test that was described in Chapter 3, requires two steps:
In this chapter we will carefully estimate the level of significance and the relative power of this adaptive test for testing a slope in a simple linear regression and for testing coefficients in a multiple linear regression. We will also show how these can be performed in R and in SAS. We begin by describing the weighting procedure in detail.
In this section we will use matrix notation to describe the linear models. Let Y be the n × 1 vector for the dependent variable, let X be the n × q matrix of independent variables, and let β be the q × 1 vector of regression coefficients. With this notation the. linear model can he written as ...