In some fields of in vitro and cell-based preclinical research direct replication attempts are uncommon and thus bias is difficult to assess empirically. Conversely, there are often multiple animal model studies performed on similar questions. Empirical evaluations have shown that small studies consistently give more favorable results than larger studies [36] and study quality is inversely related to effect size [37–40]. A large-scale meta-epidemiological evaluation [38, 41] used data from the Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Studies consortium (CAMARADES; http://www.camarades.info/). It assessed 4,445 datasets synthesized in 160 meta-analyses of neurological disorders, and found clear evidence of an excess of significance. This observation suggests strong biases, with selective analysis and outcome reporting biases being plausible explanations.
