Magnetic resonance imaging
(MRI) is a medical
imaging technique which uses magnetic fields to look at organs in a living
body. This post describes the math behind a particular MRI imaging technique
called Diffusion Tensor Imaging (DTI). DTI is used to map the structure of the
brain by measuring how restricted the water molecules are in their local
environment. It is a clever technique as it relies on taking a bunch of
overexposed images from many different directions and then using a statistical
model to try and recover what the water molecules are doing. If we can figure
out how the water molecules move, we get an idea of the local environment that
the water molecules are in and thus build a map of the brain.
A developmental trajectory describes the course of a behavior over age or time.
Daniel Nagin pioneered a method
called Group-based Trajectory Modeling to cluster these trajectories into
groups. Link. This
method is quite popular in the medical and social sciences. In this post I will
take a look at his
paper
from 1999 - Analyzing Developmental Trajectories - A Semiparametric
Group-based approach and provide
some code in R to work through the datasets.
This post is an attempt to get R
Markdown to render on a
jekyll website. The prolific Yihui Xie has a github
repository yihui/blogdown to
demonstrate how to do this using blogdown and knitr. There is also some
documentation available.
Jekyll isn’t well supported by blogdown so I needed to hack a few things
together to get them to work well.
I’m trying to setup a blog with with many moving parts : jekyll, blogdown,
mathjax, R, python, jupyter, github-pages. I’m optimistic that if I
keep it simple they will all play well together. Time will tell..