A couple of years ago I did an experiment where I recommended times to called sampled units in a face-to-face survey based on an area probability cluster sample. The recommendations were based on estimates from multi-level logistic regression models. The interviewers ignored the recommendations.
In meetings with the interviewers, several said that they didn't follow the recommendations since they call every case on every trip to an area segment. The call records certainly didn't reflect that claim. But it got me thinking that maybe the call records don't reflect everything that happens.
Biemer, Chen and Wang (2011) reported a survey of interviewers where the interviewers did report that they do not always create a call record for a call. They reported that sometimes they would not report a call in order to keep a case alive (since the number of calls on any case was limited) or because they just drove by the sampled unit and saw that no one was home. Biemer, Chen, and Wang also show that this selective reporting of calls can damage nonresponse adjustments that use the number of calls. Making bias worse.
It seems like there are two options. 1) Understand the process that generates the call records and how errors occur (this might allow us to adjust for the errors); 2) Improve the process to remove those errors. Either way, it seems like option 1 is the first step.
In meetings with the interviewers, several said that they didn't follow the recommendations since they call every case on every trip to an area segment. The call records certainly didn't reflect that claim. But it got me thinking that maybe the call records don't reflect everything that happens.
Biemer, Chen and Wang (2011) reported a survey of interviewers where the interviewers did report that they do not always create a call record for a call. They reported that sometimes they would not report a call in order to keep a case alive (since the number of calls on any case was limited) or because they just drove by the sampled unit and saw that no one was home. Biemer, Chen, and Wang also show that this selective reporting of calls can damage nonresponse adjustments that use the number of calls. Making bias worse.
It seems like there are two options. 1) Understand the process that generates the call records and how errors occur (this might allow us to adjust for the errors); 2) Improve the process to remove those errors. Either way, it seems like option 1 is the first step.
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