Survey Methods Musings

It seems like survey folks have thought about the use of big data  mostly as a problem of linking big data to survey data. This is certainly a very useful thing to do. The model starts from the survey data, and adds big data. This reduces the burden on respondents and may improve the accuracy of data. But I am also having conversations that start from big data, and then fill the gaps with survey data. For instance, in looking for suitable readings on using big data and survey data, I found several interesting articles that come from folks working with big data who use survey data to validate the logical inferences they make from the data as with this study of travel based upon GPS data, or to understand missing data in electronic health records as with this study. Now I'm also hearing discussion of how surveys might be triggered by events in the big data. The survey can answer the "why" question. Why the change? This makes for an interesting idea. The big data are the...

It seems that intensive measurement is on the rise. There are a number of different kinds of things that are difficult to recall sufficiently over longer periods of time where it might be preferred to ask the question more frequently with a shorter reference period. For example, the number of alcoholic drinks consumed by day. More accurate measurements might be achieved if the questions was asked daily about the previous 24 hour period. But what is the right period of time? And how do you determine that? This might be an interesting question. The studies I've seen tend to guess at what the correct periodicity is. I think it's probably the case that it would require some experimentation to determine that, including experimentation in the lab. There are a couple of interesting wrinkles to this problem. 1. How do you set the periodicity when you measure several things that might have different periodicity? Ask the questions at the most frequent periodicity? 2. How does non...