chapter  8
8 Pages

## Non-parametric and semi-parametric regression methods: Introduction and overview

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .195

8.1 Introduction and overview

Parametric regression methods for longitudinal data have been well developed in the last 20 years. Such methods can be classiﬁed broadly as estimating equation based methods, such as generalized estimating equations (Liang and Zeger, 1986), and their extensions (Chapter 3), and mixed-eﬀects models (Laird and Ware, 1982; Breslow and Clayton, 1993; see also Chapter 4). Diggle et al. (2002) provide an excellent overview of these parametric regression methods. For recent developments, see Chapter 3 through Chapter 6.