ABSTRACT
The usual method to estimate the values of the regression coefficients, and the intercept
and slope variances, is the Maximum Likelihood method. This chapter gives a
non-technical explanation of this estimation method, to enable analysts to make informed
decisions on the estimation options presented by present software. Some alternatives to
Maximum Likelihood estimation are briefly discussed. Recent developments, such as
bootstrapping and Bayesian estimation methods, are also briefly introduced in this
chapter. In addition, these are explained in more detail in Chapter Eleven. Finally, this
chapter describes some procedures that can be used to test hypotheses about specific
parameters.
