Author Archives: Joanna Diong

Reproducible research practices in qualitative research – Part 1

Recently, I reviewed a number of research proposals in which some applied qualitative or mixed (i.e. quantitative and qualitative) methods to answer health questions. I had my “reviewer hat” on as I assessed the proposals for research quality. After 3-4 proposals, it occurred to me that while assessing quantitative research proposals for research quality and reproducible practices was straightforward, doing

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Preparing computer code for peer-review: Nature journal guidelines

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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Understanding interaction (subgroup) analysis in randomised studies

When we try to interpret findings from a study, we often like to understand whether an effect (of a treatment or test condition) might be different in subjects with different characteristics. If there was substantial variability among subjects, this may have masked a treatment effect in a select few. How can we understand effects in select groups of subjects that

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Licensing data and code on the Open Science Foundation

Research funders are beginning to require that data produced in the course of the research they fund should be made openly available. This is to encourage further discovery and exploration, as well as to extend research questions. In addition, releasing data and code can be in researchers’ interest because it provides a complete and transparent record of how the conclusions

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Why we need to report more than “Data were analysed by t-tests or ANOVA”

T-tests and analysis of variance (ANOVA) are common statistical tests in physiology and biomedical science. While the SAMPL guidelines for reporting statistical analyses and methods in published literature state authors should “describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to verify the reported results”, such recommendations are rarely implemented. Simply stating

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Research concepts: Confidence interval of a mean

In previous posts, we learned that the aim of statistics is to extrapolate properties of samples to make inferences about population. However, random variation in individuals in the population produces sampling error, which means a single sample may not accurately reflect properties of the population. When data are binary, we learned how the 95% confidence interval (CI) of a sample

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