Razib Khan at Discover highlights a Psychological Science paper(1) by Simmons and Simonsohn of Penn and Nelson of Berkeley that outlines ways to institute more rigor in studies. They write:
In this article, we accomplish two things. First, we show that despite empirical psychologists' nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.
Khan discusses the recommendations, which seems obvious, but they must not be or they wouldn't merit an article, like: decide the rule for terminating data collection before data collection begins and report this rule in the article; list all variables collected; If an analysis includes a covariate, authors must report the statistical results of the analysis without the covariate, and more. Give him a read.
The problem of false positives - Razib Khan, Discover
(1) Citation: Simmons JP, Nelson LD, Simonsohn U., 'False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant', Psychol Sci. 2011 November 2011 22: 1359-1366, first published on October 17, 2011 doi:10.1177/0956797611417632