FlowingData extracts a statistics lesson on probability from a piece in FiveThirtyEight about risk assessment and criminal sentencing.
Archive for the 'Methodology' Category
Multidimensional poverty measurement and analysis is evolving rapidly. Quite recently, a particular counting approach to multidimensional poverty measurement, developed by Sabina Alkire and James Foster, has created considerable interest. Notably, it has informed the publication of the Global Multidimensional Poverty Index (MPI) estimates in the Human Development Reports of the United Nations Development Programme since 2010, and the release of national poverty measures in Chile, Mexico, Colombia, Bhutan and the Philippines. The academic response has been similarly swift, with related articles published in both theoretical and applied journals.
The high and insistent demand for in-depth and precise accounts of multidimensional poverty measurement motivates this book, which is aimed at graduate students in quantitative social sciences, researchers of poverty measurement, and technical staff in governments and international agencies who create multidimensional poverty measures.
Scott Keeter, Pew Research Center’s director of survey research, discusses declining response rates and what it means for survey reliability.
The Apple Research Kit allows researchers to develop an iPhone app, which interested respondents can download from the Apple Store. The respondent goes through an on-line consent form and then responds to questions, tasks (walking), etc. Some of the diagnostic tools are based on previously developed apps from the Apple Healthkit.
As of now, apps have been developed for collecting data for research projects on asthma, cardiovascular disease, diabetes, Parkinson’s, mind, body, and wellness after breast cancer, and for a population-based study, the LGBTQ population.
Here is a description of the informed consent process for these iPhone apps:
Participant-Centered Consent Toolkit
Listed below are a few press releases associated with the Pride Study – the population based study of the gay population. Following those posts are some more general critiques of this way of gathering data. The post from the Verge is probably the most critical raising issues of “on the internet no one knows you are a dog” and gaming the consent process (lying about eligibility for the study). On the plus side, the participant pool is going to be easier to sign up and won’t be limited to those who live close to research hospitals. Here is an excerpt from Business Insider to the reaction to the app launch for the Stanford Heart study:
It’s really incredible … in the first 24 hours of research kit we’ve had 11,000 people sign up for a study in cardiovascular disease through Stanford University’s app. And, to put that in perspective – Stanford has told us that it would have taken normally 50 medical centers an entire year to sign up that many participants. So, this is – research kit is an absolute game changer.
The participant pool is limited to iPhone users (no android version of these apps), although some will have a web interface (the Pride Study).
Launch of the Pride Study
UCSF Researchers Launch Landmark Study of LGBTQ Community Health
Jyoti Madhusoodanan | UCSF Press Release
June 25, 2015
A big LGBT health study is coming to the iPhone
Stephanie M. Lee | BuzzFeed
June 25, 2015
How The iPhone Is Powering A Massive LGBT Health Study
Kif Leswing | International Business Times
June 25, 2015
Critiques of the Apple ResearchKit
Apple’s new ResearchKit: ‘Ethics quagmire’ or medical research aid?
Arielle Duhaime-Ross | The Verge
March 10, 2015
What is the Matter with Polling?
Cliff Zukin | New York Times
June 20, 2015
This article focuses on political polling – and predictions from political polls, but much of the content is relevant to other sorts of telephone-based opinion surveys, many of which are used by social scientists: Survey of Consumers, Pew, Gallup, etc.
The article focuses on (a) the move from landline to cellphones; (b) the growing non-response rate; (c) costs; (d) and sample metrics, e.g., representativeness.
The decline in landline phones makes telephone surveys more expensive since cell phones cannot be reached through automatic dialers. The landline phone vs cellphone distribution comes from the National Health Interview Survey. Here’s a recent summary of the data. The article summarizes this as “About 10 years ago. . . . about 6 percent of the public used only cellphones. The N.H.I.S. estimate for the first half of 2014 found that this had grown to 43 percent, with another 17 percent “mostly” using cellphones. In other words, a landline-only sample conducted for the 2014 elections would miss about three-fifths of the American public, almost three times as many as it would have missed in 2008.”
The other issue for polling is the growing non-response rate.
When I first started doing telephone surveys in New Jersey in the late 1970s, we considered an 80 percent response rate acceptable, and even then we worried if the 20 percent we missed were different in attitudes and behaviors than the 80 percent we got. Enter answering machines and other technologies. By 1997, Pew’s response rate was 36 percent, and the decline has accelerated. By 2014 the response rate had fallen to 8 percent.
Non-response makes surveys more expensive – more numbers to call to find a respondent and many of them dialed by hand if it is a cellphone universe. And, most important, is the representativeness of the sample that the survey ends up with. So far, surveys based on probability samples seem to still be representative, at least based on comparing sample characteristics to gold-standard benchmarks like the American Community Survey (ACS). Participation in the ACS is mandatory, although for the last several years, Republicans in the House have tried to remove this requirement. Canada did away with its mandatory requirements with its census, with disastrous results. The following is a compilation of posts related to the mandatory response requirement in the US and Canada: [Older Posts]
The following are collection of news stories on how the Census Bureau is planning to collect data on race. It is misleading to say that the Census Bureau will not collect data on race. Instead, of asking about Hispanic Origin and Race, the Census Bureau is likely to ask about “categories” that describe the person.
And, a new category might be “Middle Eastern or North African.”
The Census Bureau collects data on all sorts of topics, but the Office of Management and Budget (OMB) makes the final call on how the concept is measured by the Federal Statistical System. Links to the Census Bureau’s submission to OMB and a report based on internal research follow a nice summary by Pew.
Census considers new approach to asking about race – by not using the term at all
D’Vera Cohn | Pew Research Center
June 18, 2015
2010 Census Race and Hispanic Origin Alternative Questionnaire Experiment
from the 2010 Census Program for Evaluations and Experiments
Feb 28, 2013
National Content Test
Submission for OMB Review | Federal Register
May 22, 2015
The Pew Research Center Fact Tank examines findings by David Swanson which uses 1910 and 1920 Census data to estimate the population of Hawaii in 1778, the year Capt. James Cook arrived.
In this case, Swanson took a detailed look at the 1910 and 1920 U.S. Census’s Native Hawaiian counts, tracking the survival rate of each five-year age group from one census to the next. For example, he looked at how many children who were newborns to age 4 in 1910 were counted as 10- to 14-year-olds in 1920, then did the same for each successive age group. For each group, he created a “reverse cohort change ratio,” which he used to go back in time and estimate the size of each age group for each decade until he got to 1770.
The article also reports on the growth of the Native Hawaiian population since the 1980s.
The Pew Research Center has been experimenting with mobile apps for “signal-contingent experience sampling” to gather data about how Americans use their smartphones. They have just released a report examining the possibilities of this method:
This report utilizes a form of survey known as “signal-contingent experience sampling” to gather data about how Americans use their smartphones on a day-to-day basis. Respondents were asked to complete two surveys per day for one week (using either a mobile app they had installed on their phone or by completing a web survey) and describe how they had used their phone in the hour prior to taking the survey. This report examines whether this type of intensive data collection is possible with a probability-based panel and to understand the differences in participation and responses when using a smartphone app as opposed to a web browser for this type of study.
The is an excellent summary of the consequences of the demise of the 3-year ACS tabular products. Please follow through and contact the relevant government officials:
ACS 3-Year Summary Products: Please take action to save the ACS 3-year data products
Steve Ruggles | PAA President and Director of the Minnesota Population Center
March 4, 2015
Gentrification in America Report
Mike Maciag | Governing
This resource is city-specific and provides both counts and maps of gentrified census tracts for the 50 largest cities. To be eligible for gentrification a census tract’s median household income and median home value were both in the bottom 40th percentile of all tracts within a metro area at the beginning of the decade. The gentrified tracts recorded increases in the top third percentile for both measures when compared to all others in a metro area.
And more broadly, this resource has a special issue on gentrification:
The G-Word: A Special Series on Gentrification
The titles in this series are:
Do Cities Need Kids?
The Neighborhood Has Gentrified, But Where’s the Grocery Store?
Just Green Enough
Gentrification’s Not So Black and White After All
The Downsides of a Neighborhood ‘Turnaround
Some Cities Are Spurring the End of Sprawl
Keeping Cities from Becoming “Child-Free Zones”
From Vacant to Vibrant: Cincinnati’s Urban Transformation
Can Cities Change the Face of Biking?