Consider the sample of two binary variables X and Y with some missing structure within X or Y. The knowledge about the corresponding values of the observed covariate allows to play through all possible originally' complete data sets. After defining the notation, including some theoretical work,...

I review assumptions about the missing-data mechanisms that underlie methods for the statistical analysis of data with missing values. I describe Rubin's original definition of missing at random (MAR), its motivation and criticisms, and his sufficient conditions for ignoring the missingness...

The quality of historical US census data is critical to the performance of linking algorithms. We use genealogical profiles to correct measurement errors in census names and ages. Our findings suggest that one in every two records has an error in name or age, and human capital is correlated with...

In longitudinal studies, analysis can be based on any one of a large number of wavecombinations. However, only one set of non-response weights (often based on respondents from all waves up to the latest) is typically offered on public use data files. We refer to this as a single weighting...