Fixed Effects Regression Methods for Longitudinal Data Using SAS

1.6. What You Need to Know

To understand this book, how much you should already know depends on how far you want to go. To read chapter 2 on linear models, you need to be familiar with multiple linear regression. That means that you should know something about the assumptions of the linear regression model and about estimation of the model via ordinary least squares. Ideally, you should have a substantial amount of practical experience using multiple regression on real data and should feel comfortable interpreting the output from a regression analysis. As part of this knowledge, you must certainly know the basic principles of statistical inference: standard errors, confidence intervals, hypothesis tests, p-values, bias, efficiency, and so on. ...