I’ve had a lot of different jobs over the past 4 years, and I’ve had some incredible experiences along the way. Lately, I’ve been struggling with what to do next. Or perhaps more accurately, I’ve been struggling with how to de...

In the last episode (which was quite some time ago) we looked into comparisons of means with linear models. This time, let’s visualise some linear models with ggplot2, and practice another useful R skill, namely how to simulate data from known models. While doing this, we’ll learn some more about the layered structure of a

Last week I looked at two-way cross-over studies and followed the example of Schütz (http://bebac.at/) in the analysis. Since the EU has its on opinions (Questions & Answers: Positions on specific questions addressed to the pharmacokinetics working party) and two example data sets, I was wondering how the various computations compared.Data There...

I am doing a second installment of the lunch seminars about data analysis with R for the members of the Wright lab. It’s pretty much the same material as before — data frames, linear models and some plots with ggplot2 — but I’ve sprinkled in some more exercises during the seminars. I’ve tried emphasising scripting a

I ran into this presentation on Statistical aspects of two-way cross-over studies by Ing. Helmut Schütz (http://bebac.at). He presented some code and referred to the bear package. The bear package is menu driven, which is not my thing. I had to try and do that in R via other packages. The aim is to estimate if the...

I’m often irritated by that when a statistical method is explained, such as linear regression, it is often characterized by how it can be calculated rather than by what model is assumed and fitted. A typical example of this is that linear regression is often described as a method that uses ordinary least squares to calculate the best...

MilanoR, in collaboration with Quantide, organizes "Statistical Models with R" Course October 24-25, 2013 Course description This two-day course shows a wide variety of statistical models with R ranging from Linear Models (LM) to Generalized Linear Models (GLM) modelling, in … Continue reading →

The title of this book Informative Hypotheses somehow put me off from the start: the author, Hebert Hoijtink, seems to distinguish between informative and uninformative (deformative? disinformative?) hypotheses. Namely, something like H0: μ1=μ2=μ3=μ4 is “very informative” and the alternative Ha is completely uninformative, while the “alternative null” H1: μ1<μ2=μ3<μ4 is informative. (Hence the < signs on