Multiple sclerosis
is an autoimmune complex disease that affects the central nervous
system. It has a multitude of symptoms that are observed in different
people in many different ways. At this time, there is no definite cure
for multiple sclerosis.
However, therapies that slow the progression of disability, controlling
symptoms and helping patients to maintain a normal quality of life, are
available. We will focus on relapsing-remitting multiple sclerosis
patients treated with interferons or glatiramer acetate. These
treatments have been shown to be effective, but their relative
effectiveness has not been well established yet. To assess the
superiority of a treatment, instead of classical parametric methods, we
propose a statistical approach within the permutation setting and the
nonparametric combination of dependent permutation tests. In this
framework, we may easily handle with hypothesis testing problems for
multivariate monotonic stochastic ordering. This approach has been
motivated by the analysis of a large observational Italian multicentre
study on multiple sclerosis, with several continuous and categorical outcomes measured at multiple time points.
I am not going to try and put this into a language that you can understand as it zips over my head. Rather than finding more and more convoluted ways of showing someting, the smack you in the eye test is always good, if you can't easily see a difference it isn't there.
Labels: statistics