In my last post, I talked about how errors in call records might lead to bad things. If these errors are biasing (i.e. interviewers always underreport and never overreport calls -- which seems likely), then adjustments based on call records can create (more) bias in estimates. I pointed to the simulation study that Paul Biemer and colleagues carried out. They used an adjustment strategy that used the call number.

There are other ways to use the data from calls. For instance, if I'm using logistic regression to estimate the probability of response, I can fit a model with a parameter for each call. Under that approach, I'm not making an assumption about the relationship between calls and response. It's like the Kaplan-Meier estimator in survival analysis. If there is a relationship, then I can fit a logistic regression model with fewer parameters. Maybe as few as one if I think the relationship is linear. That smooths over some of the observed differences and assumes they ar…

There are other ways to use the data from calls. For instance, if I'm using logistic regression to estimate the probability of response, I can fit a model with a parameter for each call. Under that approach, I'm not making an assumption about the relationship between calls and response. It's like the Kaplan-Meier estimator in survival analysis. If there is a relationship, then I can fit a logistic regression model with fewer parameters. Maybe as few as one if I think the relationship is linear. That smooths over some of the observed differences and assumes they ar…