A post by Sunmoo Yoon in the NIH OBSSR blog looks at the potential of data mining to offer insights into predictors of physical activity in older urban adults:
Only two out of ten older adults meet the national guidelines for physical activity in the United States. Little is known about interrelationships of many socio-ecological factors to improve physical activity behavior among Hispanic older adults. As we move towards a precision medicine approach, we need innovative strategies to discover precisely tailored targets and accurate interventions. Data mining has the potential to offer such insights.
This is a nice tool for getting net migration reports based on IRS tax return data. Note that because these data are based on tax returns, one can also tell whether, on average, a state is losing/gaining wealthier residents. One can generate reports for counties by state or for states. The former is really tedious because one has to generate the county reports one by one.
Counties | States
And here’s the link to raw data for those who find widgets tedious. Note that the site has nice explanations for the methodology, including changes over time in how these files are created: SOI Tax Stats – Migration Data
And, do you want to know how to make something like the map above? Here’s a link from Flowing Data on how to make a similar map based on 5-years of county-to-county IRS data:
Article | How To Guide
As of 9/30/2016, Easy Stats will no longer be available. To access data from the American Community Survey, use American FactFinder or QuickFacts. You can provide feedback here.
According to Data Detectives, “The retirement of the application is a result of a CEDSCI data tools assessment from earlier this year. The assessment looked at consolidating data tools to eliminate redundancy and also streamline our data dissemination offerings on Census.gov.”
This is a report on the NCI/SEERS web portal on a way to create residential histories of respondents/decadents for epidemiological research. The report (below) details how three commercial vendors were able to match the residential history of a small sample of federal government employees. Also available are the algorithms and software to reconcile conflicting addresses. Interested folks might want to browse other tools/papers in the NCI Geographical Information Systems and Science for Cancer Control webiste. https://gis.cancer.gov/index.html
NCI/SEER Residential History Project
David Stinchcomb and Allison Roeser | Westat
SAS residential history generation programs [3 programs]
[Summary] [Link to programs]
Nathan Yau of Flowing Data has 5 tips for for learning to code for visualization: “being able to code your own visualization carries its own benefits like flexibility, speed, and complete customization.”
Stata is holding three 2-day sessions for new users. Sessions are $950 with a 15% discount for group enrollments of three or more.
Become intimately familiar with all three components of Stata: data management, analysis, and graphics. This two-day course is aimed at both new Stata users and those who wish to learn techniques for efficient day-to-day use of Stata. Upon completion of the course, you will be able to use Stata efficiently for basic analyses and graphics. You will be able to do this in a reproducible manner, making collaborative changes and follow-up analyses much simpler. Finally, you will be able to make your datasets self-explanatory to your co-workers and yourself when using them in the future.
The May 24-25 and June 20-21 are in Washington, DC and the October 24-25 session is in Las Vegas.
Go to this site for more training courses.
The World Bank has a new interactive chart showing how the leading causes of death are changing worldwide:
From The DataBlog:
Worldwide, the leading causes of death are changing, and they vary between rich and poor countries. In low-income countries, deaths from communicable diseases such as malaria and HIV/AIDS have fallen, while deaths from non-communicable diseases such as stroke and diabetes are on the rise.
Data USA is a collaboration between Deloitte, Macro Connections at the MIT Media Lab, and Datawheel which is (according to their About page), “the most comprehensive website and visualization engine of public US Government data.” The data is pulled from sources such as the American Community Survey, the Bureau of Economic Analysis, and the Bureau of Labor Statistics, and the visualizations are powered by D3plus, an open source visualization engine.
H/T Flowing Data
Even though NIH and NSF both have data sharing requirements, there is clearly some resistance to it. The best example is an editorial from the New England Journal of Medicine. Secondary data users are characterized as “research parasites.”
A rebuttal comes from a Science editorial with the title #IAmAResearchParasite.
Dan L. Longo and Jeffrey Drazen | N Engl J Med
January 21, 2016
Marcia McNutt | Science
March 4, 2016
In advance of Super Tuesday, the U.S. Census Bureau released demographic and economic profiles of the 12 states holding primaries and caucuses:
H/T Data Detectives