Coordinated Data Analysis: A New Method for the Study of Personality and Health

Abstract

A majority of research by personality psychologists examining health has utilized publicly available datasets, for good reason. These resources are often the only available datasets large enough to detect expected effect sizes and may contain biological or genetic data that is difficult to obtain. However, researchers tend to examine only one large dataset at a time. Given recent meta-research on the robustness and replicability of "established" findings, all researchers should take greater care to evaluate the evidentiary value of their findings and seek methods to increase their robustness. Personality and aging psychologists who use publicly available datasets have a unique tool at their disposal in order to achieve this goal, namely, more publicly available datasets. More specifically, psychologists may use coordinated analysis (Hofer and Piccinin, 2009; Piccinin and Hofer, 2008) to examine relationships across several large datasets and, using the tools of meta-analysis, identify generalizable effect sizes and examine heterogeneity across countries and methods. This chapter describes the motivation for coordinated analysis, the process of using this method, and details several examples.