chasing significance

Success-vs-SignificanceAn interesting study from journal Addictionon studies:

Background and Aims
The low reproducibility of findings within the scientific literature is a growing concern. This may be due to many findings being false positives which, in turn, can misdirect research effort and waste money.

We review factors that may contribute to poor study reproducibility and an excess of ‘significant’ findings within the published literature. Specifically, we consider the influence of current incentive structures and the impact of these on research practices.

The prevalence of false positives within the literature may be attributable to a number of questionable research practices, ranging from the relatively innocent and minor (e.g. unplanned post-hoc tests) to the calculated and serious (e.g. fabrication of data). These practices may be driven by current incentive structures (e.g. pressure to publish), alongside the preferential emphasis placed by journals on novelty over veracity. There are a number of potential solutions to poor reproducibility, such as new publishing formats that emphasize the research question and study design, rather than the results obtained. This has the potential to minimize significance chasing and non-publication of null findings.

Significance chasing, questionable research practices and poor study reproducibility are the unfortunate consequence of a ‘publish or perish’ culture and a preference among journals for novel findings. It is likely that top–down change implemented by those with the ability to modify current incentive structure (e.g. funders and journals) will be required to address problems of poor reproducibility.

They offer an interesting solution:

Journals such as Cortex and Drug and Alcohol Dependence have introduced new manuscript submission formats that place the emphasis on the research question and study design, rather than the results obtained. Manuscripts (essentially protocols, containing the introduction, hypotheses, methods, analysis plan and sample size justification) are reviewed before data collection takes place, and judged on whether the results will be informative regardless of how they ultimately turn out. If acceptance-in-principle is offered, then the authors can conduct their study safe in the knowledge that, as long as they adhere to their plans, their results will eventually be published.

Deciding on whether or not to publish the results of a study before the results are known offers several important advantages. First, it ensures that publication depends on the importance of the research question being addressed, and the appropriateness of the methods chosen, rather than novelty and P-values. Secondly, it minimizes research practices that inflate the likelihood of false positives (e.g. ‘significance chasing’), given the requirement to adhere to pre-declared methods. Thirdly, the requirement for a priori power calculation to justify the sample size minimizes problems of low statistical power.

2 thoughts on “chasing significance

  1. Nice, solid idea. Still leaves the authors free to decide not to publish findings they don’t like, but that has always been the case.


  2. Statistical significance is always problematic. Any study with even a reasonable sample size can easily demonstrate statistical significance. Additionally, researchers are notorious for deciding to set their Alpha thresholds, after they figure out what they can get away with and still show significance, when in reality, Alpha should always be pre-determined in a study. Regression modeling and SEM, commonly utilized forms of statistical analysis have far too often become an exercise of throwing a bunch of variables into a stats program like SAS or SPSS and seeing what sticks, which anyone who understands even the basics of social research understands how wrong this is. Great post, and more folks need to know how to scrutinize research studies and articles in order to critique and cast light on poor studies and dishonest researchers.


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