While I truly hope not a sign of the times, as the title implies, Just Post It: The Lesson from Two Cases of Fabricated Data Detected by Statistics Alone, illustrates how simple statistical tests can be used to detect falsified data. Interestingly, Uri Simonsohn's (Penn-Wharton) main point involves a plea for journals to make available raw data used to support findings in published papers. That such a policy may assist in rooting out fraudulent papers (and deterring such unethical conduct) is a positive spillover. The abstract follows.
"I argue that journals should require authors to post the raw data supporting their published results. I illustrate some of the benefits of doing so by describing two cases of fraud I identified exclusively through statistical analysis of reported means and standard deviations. Analyses of the raw data provided important confirmation of the initial suspicions, ruling out benign explanations (e.g., reporting errors; unusual distributions), identifying additional signs of fabrication, and also ruling out one of the suspected fraudster’s explanations for his anomalous results. If we want to reduce fraud, we need to require authors to post their raw data."