Multilevel Modeling

2. Introduction

Describing area-based differences in health outcomes has a long history (Macintyre and Ellaway, 2003). We know that places differ in terms of their average health achievements, but do places make a difference?

This question has received systematic attention in the last decade or so (Duncan, Jones et al., 1993; Macintyre, Maciver et al., 1993; Diez Roux, 2001; Pickett and Pearl, 2001; Kawachi and Berkman, 2003; Lynch, Smith et al., 2004; Subramanian and Kawachi, 2004). Besides its resonance with the move to look at “upstream” determinants of health and recognizing that health behaviors and outcomes need to be understood within their context (Susser and Susser, 1996a; Susser and Susser, 1996b; Berkman and Kawachi, 2000; Kawachi and Berkman, 2003; Wilkinson and Marmot (Eds), 2003; Link and Phelan, 1995; Jones and Moon, 1987; Moon, Subramanian et al., 2005), a major impetus for examining the role of contexts in explaining health variations comes from the advances in quantitative methods, in particular those related to multilevel statistical methods (Bryk and Radenbush, 1992; Goldstein, 1995). In this chapter, we review and provide an overview of the basic principles of multilevel modeling as applied to public health research (Subramanian, Jones et al., 2003; Moon, Subramanian et al., 2005; Blakely and Subramanian, 2006).

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