Predictors of momentary missingness in a sample of breast cancer survivors

This study will use ecological momentary assessment (EMA) data from a sample of breast cancer survivors to investigate predictors of missing observations in this sample. We will use a series of multilevel logistic regression models to look for person-level, day-level, and lagged momentary predictors of a missing beep. This approach is consistent with a growing body of literature that seeks to understand predictors of missingness in EMA data.