Missing data for longitudinal surveys occur in a variety of patterns which can be sorted and categorized into different classes of missingness depending on the survey unit. For this study, the survey unit is a person. Therefore the missingness that occurs in the data can be person nonresponse, whereby no data is available for a person at any given time period in the survey, record-type nonresponse where an entire module of related data is unavailable, and item nonresponse in which data is missing sporadically throughout the person record. For this study we focused on record-type of nonresponse for a single continuous variable. It is important that these types of nonresponse to be addressed as they occur generously throughout a longitudinal survey. Also, simulation of record-type nonresponse provides a reasonably sized data files to study and manipulate. It is important to note that the techniques investigated can be employed to compensate for both item and record-type nonresponse.

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