I am seeking advice on the appropriate statistical model for a situation involving right-truncated continuous data.
The outcome variable represents the duration (in weeks) that mothers fed their children formula after childbirth. The range includes responses like 0 weeks, 10 weeks, or 35 weeks.
However, there is a measurement error in this data: some mothers reported durations that exceed the child’s age at the time of the interview. For instance, a mother was interviewed when her child was 2 weeks old but reported feeding formula for 10 weeks, the response is biologically implausible. To address this issue, we decided to truncate these responses to the child’s age. In this example, the response would be adjusted to 2 weeks.
Given this truncation process, what statistical models would be most appropriate to analyze this data? While I understand that a simple linear regression could be applied if we exclude erroneous observations, I am particularly interested in methods that explicitly account for truncation if these adjusted responses are included. I am uncertain about the applicability of survival models in this scenario, as there is no specific event being analyzed—only the duration of formula feeding. Given this, I am unsure if a survival model would be an appropriate fit.
Thanks.