ABSTRACT
The usual method to estimate the values of the regression coefficients and the intercept and slope variances is the maximum likelihood estimation method. This chapter gives a non-technical explanation of maximum likelihood estimation, to enable analysts to make informed decisions on the estimation options offered by current software. Some alternatives to maximum likelihood estimation are briefly discussed. Other estimation methods, such as Bayesian estimation methods and bootstrapping, are also briefly introduced in this chapter. Finally, this chapter describes some procedures that can be used to compare nested and non-nested models, which are especially useful when variance terms are tested.
