Generalizability and Transportability

This chapter provides an introduction to the problems of generalization and transportation and methods for addressing these concerns. The field of causal inference is one that, at its core, focuses on improving internal validity: the extent to which a study can establish a trustworthy cause-and-effect relationship between a treatment and outcome. To understand potential external validity bias, it is essential that researchers clearly define their targets of inference. Researchers can often exert more control over what variables are collected in the sample than which variables are available in the target population. Tipton and colleagues provides a case study from a situation in which the resulting samples from two separate randomized trials were quite different than the target populations the studies initially intended to represent. Questions of generalization and transportation call to question the reasons that research is conducted, the questions asked, and the ways in which research will be used for decision-making for both individuals and policies.