The experiment on call scheduling in a telephone survey required specialized programming to make it work. We use Blaise SMS in our telephone facility. My colleagues here, Joe Matuzak and Dave Dybicki, are planning to present what they did to make this experiment work at the International Blaise Users Conference (IBUC) in October.
They asked me to show some of the results. The first problem we faced was how to make sure that the experimental and control groups were called at the same pace. I produce files every day that show how I want the sample sorted. The control group is sorted using a different algorithm. But we had to make sure that the cases were mixed up -- we didn't want to call one group and then the other.
Dave wrote a program that reads the sorted list for each group (experimental and control). It pulls a record from each list and then checks if it is still active. Maybe it was finalized after the sort occured. When it finds 5 active cases from the top of the sort in one group, it pulls 5 active cases from the other group. It continues this process until the whole sample is sorted, with 5 active experimental cases followed by 5 control cases. Or vice versa.
The following table shows the proportion of calls to each type of case by hour. I'm ignoring day of week (mainly weekend vs weekday) just to simplify the table.
It looks like the algorithm works pretty well at keeping the distribution of calls even across hours of the day. There were some other jazzy features that Dave and Joe set up for the experiment. You'll have to catch their presentation at IBUC if you want to learn more about those.
They asked me to show some of the results. The first problem we faced was how to make sure that the experimental and control groups were called at the same pace. I produce files every day that show how I want the sample sorted. The control group is sorted using a different algorithm. But we had to make sure that the cases were mixed up -- we didn't want to call one group and then the other.
Dave wrote a program that reads the sorted list for each group (experimental and control). It pulls a record from each list and then checks if it is still active. Maybe it was finalized after the sort occured. When it finds 5 active cases from the top of the sort in one group, it pulls 5 active cases from the other group. It continues this process until the whole sample is sorted, with 5 active experimental cases followed by 5 control cases. Or vice versa.
The following table shows the proportion of calls to each type of case by hour. I'm ignoring day of week (mainly weekend vs weekday) just to simplify the table.
It looks like the algorithm works pretty well at keeping the distribution of calls even across hours of the day. There were some other jazzy features that Dave and Joe set up for the experiment. You'll have to catch their presentation at IBUC if you want to learn more about those.
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