 Another reason for not pooling the data is that study populations are often heterogenous and that calculating the strength of association (i.e., the effect size) on the basis of the data may bias the estimate in the direction of the study with the largest sample size, while the characteristics of patients in that study need not be representative of the target group as a whole. In particular, while at the level of studies patients are usually assigned randomly to the treatment or control group, this cannot be said about the aggregate data (Cates 2002). Proper meta-analysis therefore proceeds on the basis of weighting the effects rather than pooling the data, either by a fixed effects model or (e.g., if the study populations are heterogenous) by introducing a random effect of the study in the statistical model. The question of how to conduct a meta-analysis of epidemiological studies is also entangled with the choice of an association or effect size measure (Altman &amp; Deeks 2002; Cates 2002; Greenland 1987), a question discussed in  Section 2.2.