Underpowered studies are a big (but far from the only) source of the current replication crisis in the medical literature. Power calculations hinge on the expected effect size (often expressed as Cohen’s d), the populations’ spread around the mean (standard deviation) and arbitrary frequentist assumptions about alpha and beta. Cohen’s d is conceptually similar to…
It is hard to quickly evaluate data in an everyday situation, but a nifty shortcut I saw on the R-bloggers aggregator can help. In the simplest example, suppose you toss a coin 50 times with 32 heads and 18 tails. What are the chances the coin is fair? The handy shortcut helps to quickly evaluate…
For a simple exercise to understnad one-way ANOVA, I will use the data set red.cell.folate from the package ISwR (see the book “Introductory Statistics with R” by Peter Dalgaard) but will also generate our own data. And now (drum roll) … it’s time to run the ANOVA Let’s look at what this ANOVA table means….
“Classical” statistical inference in medicine is usually synonymous with frequentist inference, the central element of which is the null hypothesis significance testing (NHST). Even though that was not its original intent, NHST is in practice used to evaluate the evidence for or against a hypothesis, due to confusion in mixing Fisher’s approach with that of…
