We chose our company name, Creascience to emphasize that creativity can mix efficiently with science. In this blog, we share illustrations of how a correct use of statistics leads to drastic improvements of scientific research. Come back often to read our latest findings or simply follow this link to get notified by email (guaranteed 100% ad-free).
Power Failure: Why Small Sample Size Undermines the Reliability of Neuroscience
The issues discussed in this paper are clearly not only prevalent in neuroscience… I know that this is a 2013 paper and hopefully the situation has improved, but allow me to seriously doubt it. Nevertheless, I decided to post it because of the general nature of the problems and also because this is an easy…
Reporting Experimental Designs in Scientific Publications
Scientific rigour is a major concern and most scientific journals have a policy on statistical analysis and data representation to ensure that issues of experimental design can be reviewed thoroughly. Experimental design is one crucial component of a scientific method. “A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate…
The Winner’s Curse: Effect Size Inflation as a Function of Statistical Power
Consequences Illustration The figure shows simulations of the winner’s curse (expressed on the y‑axis as relative bias of research findings). These simulations suggest that initial effect estimates from studies powered between ~ 8% and ~31% are likely to be inflated by 25% to 50% (shown by the arrows in the figure). Inflated effect estimates make…
Error Bars in Science – Erroneous Display?
Today I would like to focus on the confusing reporting of findings using mean +/- error bars. Error bars are graphical representations that can help convey information about the variability or uncertainty in data. They are used in charts, graphs, or plots to show the range of values within which the true value of a…
Statistical Terminology for ANOVA (lm), glm, glmm & Beyond
I would like to propose alternatives to what is unfortunately very common in scientific papers “An ANOVA was done/…” Hopefully, the terminology below should help investigators improving the reporting of statistical modelling in R&D. This goes beyond ANOVA. Terminology Reference Tracey L Weissgerber, Oscar Garcia-Valencia, Vesna D Garovic, Natasa M Milic, Stacey J Winham (2018)…
Reproducible Summary Tables with the gtsummary Package in R
The reproducibility of scientific results depends on several factors. One such factor is the consistency and accuracy of the reported results. Those of you who run statistical analyses, fit models and report results in scientific publications know that there are many risks of errors when reporting results as copy/paste are usually required.– The CIs may…