Parametric Survival Analysis of a Sleep Diary
Introduction # As a teenager, I began to suffer with chronic and ongoing insomnia that has stayed with me for all of my adult life with very few periods of real respite. However, rather than turn this into a sob story, I’ve managed to come up with a really interesting data story! In the search for triggers and patterns, I decided to buy a wearable fitness tracker and keep a tally of my nightly quality sleep hours. Around the same time, I finally had the self-awareness to realise that a lot of my worst nights seemed to be accompanied by digestive disturbances, even so to hypothesise that certain food groups may be acting as triggers or exacerbating the problem. I decided to keep a food diary alongside the sleep data. I might also add that I’m proud of myself for not skipping a day during the collection period.
Round Peg in a Square Hole
Introduction # This post is a prologue to a forthcoming post on survival analytics and featucres the exploratory analysis of a self-generated data set that I will use for another demonstration post in the next few weeks. Let me give you the background quickly, because I will go deeper with the next post: I have a really chronic problem with insomnia, since I was a teenager. I had a sense that certain foods were triggering bad nights’ sleep so I kept a food diary of what I’d eaten for dinner and recorded my quality sleep hours with a fitness tracker for a year.
Statistical Learning for Heart Disease Diagnosis
Author’s Note (October 2020): In preparation for work on my published research paper Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences, I wanted to develop some familiarity with medical statistics and diagnostic tools. I decided to take a fairly well-known medical data set and try something different. Instead of performing a straightforward classification model training as would be typical, I took a deep exploratory dive. My intention was to see if I could tease out some intuition as to what were the predictive patterns in the data. The exercise evolved into a potential approach to developing a statistical diagnostic tool, for similarly distributed data. My original report is reproduced below.
Freelancing In Paradise
I took a career break while I was still living in the tropics and had the chance to do some freelance work in between SCUBA dives. One of my first gigs was to help a client to evaluate their sales target setting process. Their team was split into two groups and some rumours were circulating that one group had their targets set too easy. I was able to recommend some improvements based on some very simple statistical tests.
Be Inclusive, Be Change
Recently, I had the opportunity to work with B-Change.org (a.k.a. Be-Inclusive.org) to clarify and focus strategy and positioning for their mobile app. B-Change strives to help marginalized groups, to feel more connected. Their app was intended to be a relaunch of a community web-site that served the Southeast Asian LGBT and HIV-positive youth community by offering them information about service providers who are more sympathetic to their specific needs. The app helped B-Change to deliver a much more socially connected experience with a renewed focus on user genenarated content but they were struggling with user adoption and traction.