On the policy side, we have also seen shifts that support greater use of pooled data analysis. For example, a fundamental issue in conducting pooled data analysis is data sharing. In line with ethical guidelines (American Psychological Association, 2002), top-tier journals in clinical psychology (e.g., Journal of Abnormal Psychology and the Journal of Consulting and Clinical Psychology) and federal funding agencies (NIH, 2003; NSF, 2011) have long encouraged data sharing to monitor the quality and veracity of published findings. But recent efforts extend the goals of data sharing to generating data structures that encourage pooled data analysis. For example, NIH currently provides support for building “metadata structures” through initiatives that “assist in data retrieval and pooled data analysis across sites” (RFA-HD-10-001; NICHD, 2010) and encourages applicants “to collaborate with investigators holding private data sets, use innovative statistical strategies to link methodologically comparable datasets, or utilize public use data readily available” (PAR-10-018; NIDA, 2010). Other NIH initiatives have established data repositories for GWAS studies (the Database for Genotypes and Phenotypes, dbGAP; Mailman et al., 2007), autism research (the National Database for
