In my last post, I talked about the costs of collecting interviewer observations. These observations have to reduce total survey error (likely nonresponse error) in order to justify this cost.
The original definition of paradata was that it was a by-product of the data collection process. Computers stored information on keystrokes at basically no extra cost. Call records were necessary to manage the data collection process, but they were also found to be useful for developing nonresponse adjustments and other purposes.
At some point, interviewer observations became paradata. I think many of these observations started out as information that interviewers recorded for their own purposes. For example, listers would record if there were any barriers to entering the segment (e.g. gated communities or locked buildings) so that interviewers would know about that before traveling to the segment. These could be thought of as no cost.
But we have added a lot of observations that the interviewers don't need for their purposes. These are strictly designed for nonresponse monitoring and adjustment purposes. These do require time and effort for interviewers to record them.
It might be good to think about more ways to passively collect useful data. Smartphones, for instance, can collect many new kinds of data. I accidentally came across this article on the use of smartphones in research and this one as a recent example. Perhaps these sorts of passive data collection can be harnessed to provide useful data for monitoring and adjusting for nonresponse.
The original definition of paradata was that it was a by-product of the data collection process. Computers stored information on keystrokes at basically no extra cost. Call records were necessary to manage the data collection process, but they were also found to be useful for developing nonresponse adjustments and other purposes.
At some point, interviewer observations became paradata. I think many of these observations started out as information that interviewers recorded for their own purposes. For example, listers would record if there were any barriers to entering the segment (e.g. gated communities or locked buildings) so that interviewers would know about that before traveling to the segment. These could be thought of as no cost.
But we have added a lot of observations that the interviewers don't need for their purposes. These are strictly designed for nonresponse monitoring and adjustment purposes. These do require time and effort for interviewers to record them.
It might be good to think about more ways to passively collect useful data. Smartphones, for instance, can collect many new kinds of data. I accidentally came across this article on the use of smartphones in research and this one as a recent example. Perhaps these sorts of passive data collection can be harnessed to provide useful data for monitoring and adjusting for nonresponse.
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