New in episensr 0.9.3 - E-value

New version of episensr available on CRAN! In the same vein than the other new function based on the work from Schneeweiss, this new version allows the computation of the E-value as proposed by VanderWeele and Ping, 2017. The E-value is the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific exposure-outcome association, conditional on the measured covariates. Read More

New in episensr 0.9.3 - Array approach for unmeasured confounders

New version of episensr available on CRAN! Besides now being easier to run multiple bias analysis, this new version offers the option to check the effect of residual confounding based on the array approach (Schneeweiss, 2006). Even after controlling for confounding (in the design or analysis of a study), some residual confounding can still be present, because: some confounding factors were not taken into account (not looked at, not adjusted for, or no data collected about them), you only losely took into account that confounding (still presence of differences between groups after control by matching for example, or you lost precision on a confounding variable e. Read More

New in episensr 0.9.3 - Multiple bias analysis

New version of episensr available on CRAN! Now you can more easily run multiple bias analysis. Very often, epidemiologic studies suffer from multiple biases. Up to now, it took a bit of “manipulation” to apply a sequence of bias function from episensr. So here’s the function multiple.bias that allows to pipe corrected 2-by-2 table from one bias function to an other. Let’s take for example the study from Chien et al, 2006 looking at the association between antidepressant use (AD) and breast cancer (BC): Read More

Popularity of statistical softwares in epidemiology

Bob Muenchen has a series of articles on the Popularity of Data Science Software. He found that SPSS is the most used software, followed by R, SAS, Stata, GraphPad Prism, and MATLAB, by looking at scholarly articles in Google Scholar. He presents his methodology here. While he’s showing popularity (or market share) of several softwares for data science, statistical analysis, machine learning, artificial intelligence, predictive analytics, business analytics, and business intelligence, I was always wondering what the results would be like for my specific field, epidemiology. Read More

Scientific collaboration patterns in cattle health research in Canada

I was curious to see if I could identify some patterns of collaboration and research topics in cow health research made in Canada. For this, I’m trying the R package bibliometrix. This package allows quantitative research in scientometrics and bibliometrics by providing different routines for importing bibliographic data from Scopus and ISI Web of Knowledge databases, and performing various bibliometric analyses. The Bibliometrix website provides a good tutorial that I will mainly follow, with the sole objective to satisfy my curiosity and have fun! Read More