I'm really enjoying this article by Andresen and colleagues on the costs and errors associated with tracking (locating panel members). They look at both sides of the problem. I think that is pretty neat.
There was one part of the article that raised a question in my mind. On page 46, they talk about tracking costs. They say "...[t]he average tracing costs per interview for stages 1 and 2 were calculated based on the number of tracing activities performed at each stage." An assumption here -- I think -- is that each tracing activity (they list 6 different manual tracing activities) takes the same amount of time. So take the total time from the tracing team, and divide it by the number of activities performed, and you have the average time per activity.
This is perfectly reasonable and fairly robust. You might do better with a regression model predicting hours from the types and numbers of activities performed in a week. Or you might ask for more specific information on timesheets.
I'm not a fan of the latter approach. It generally costs more money to track costs that carefully, and the cost measures might be inaccurate. "How long did it take you to do X?" might have inaccurate answers. There has to be some benefit to having those data that can justify the costs. Of course, you can't justify the added cost without the data, so it can be a classic chicken or egg problem. In these situations, if feasible, it might be nice to do a special study of costs -- gather them experimentally or have observers to more detailed study.
There was one part of the article that raised a question in my mind. On page 46, they talk about tracking costs. They say "...[t]he average tracing costs per interview for stages 1 and 2 were calculated based on the number of tracing activities performed at each stage." An assumption here -- I think -- is that each tracing activity (they list 6 different manual tracing activities) takes the same amount of time. So take the total time from the tracing team, and divide it by the number of activities performed, and you have the average time per activity.
This is perfectly reasonable and fairly robust. You might do better with a regression model predicting hours from the types and numbers of activities performed in a week. Or you might ask for more specific information on timesheets.
I'm not a fan of the latter approach. It generally costs more money to track costs that carefully, and the cost measures might be inaccurate. "How long did it take you to do X?" might have inaccurate answers. There has to be some benefit to having those data that can justify the costs. Of course, you can't justify the added cost without the data, so it can be a classic chicken or egg problem. In these situations, if feasible, it might be nice to do a special study of costs -- gather them experimentally or have observers to more detailed study.
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