Contributing to journal peer review is a good way to observe and mitigate the research conducted in a scientific field, and contribute to the growth of knowledge. I have peer reviewed for some years, and assessing manuscripts for publication now comes more easily. As a peer reviewer, I think it curious how simple statistical oversights are common at submission. As
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In the previous post we learned that qualitative studies can be reported in ways to ensure research design, measurement, data analysis and data itself are made transparent. Economics researchers Aguinis and Solarino conducted a literature search and developed 12 criteria for research transparency, covering research design, measurement, data analysis and data disclosure. They emphasize that transparency exists on a continuum.
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I am used to confused interactions, likely because I get along better with dogs and kids than I do with adults. But that is not what Nieuwenhuis et al. had in mind when they surveyed 513 articles relating to behavior, cognitive function or brain imaging from leading journals (Nature, Science, Nature Neuroscience, Neuron, Journal of Neurosience). What they were looking
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For better or worse, our mind plays tricks on us: we are prone to cognitive biases and logical fallacies. These biases don’t impact how do the laundry or prepare supper, although I may convince myself that I always intended to make a galette despite having the cookbook open at the soufflé page. Unfortunately, these same biases and fallacies can wreck
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Scientific impact is a difficult thing to measure. Nevertheless, a variety of indexes and metrics have been created that attempt to quantify it. Many of these measures are based on citations: the number of times a scientific paper is referenced by another scientific paper. Unfortunately, it is not entirely clear what these citation-based metrics actually reflect, nor is it clear
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Computer code is used to analyse data in research studies across many fields including epidemiology, biomedical science, computational biology and physics. Many findings now depend on such analyses. What role do journals play in ensuring transparency and reproducibility of computer code used to generate research findings? How might this fit in with our efforts, as scientists, to reduce errors in
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