I've been working on primarily the same project throughout this time. Trying to find the total number of discrepancies in smoking status was pretty tricky, but I was able to find this number after doing some research and much perseverence (yay!). I also took some time to learn how to use knitr, a package in R that allows me to create html documents so I can easily share my code and results and reduce risk of error. As a group we also submitted a proposal  to the undergraduate research conference at our university.

This week I will finish the functions in R that I began to code this week to check for patients with smoking discrepancies, I will also begin to write a function to check for total numbers of discrepancies. Lastly I will write a report for the discrepancies for diabetes status.

Last week I began to brainstorm on ways to attack the problem of smoking status. This week I will be meeting with an outside professor to get some advice on how to go about doing this. I will also be rerunning the analysis on the diabetes discrepancies and creating a report on the findings.

This week I will begin to work on the problem of finding discrepancies of smoking statuses. In our weekly meeting we discussed some of the challenges that will come with this - primarily that smoking status can change in a much more complicated way than diabetes status. In the case of diabetes the patient must have had diabetes, so if they did not we knew there was a discrepancy. Smoking status, on the other hand, can switch back and forth many times However, if a patient is listed as a smoker in the first visit, and then as never having smoked in any later visits then there is a discrepancy. This is definitely going to be an interesting project.

These weeks were spent writing code in R in order to look for discrepancies pertaining to the diabetes status of the patients in our corpus. I met a few bumps in the road but was able to collaborate with an R expert and found a solution. I also learned of the perils of using loops and R!