TY - JOUR T1 - Itemwise conditionally independent nonresponse modeling for multivariate categorical data JF - Biometrika Y1 - 2017 A1 - Sadinle, M. A1 - Reiter, J. P. KW - Identification KW - Missing not at random KW - Non-parametric saturated KW - Partial ignorability KW - Sensitivity analysis AB - With nonignorable missing data, likelihood-based inference should be based on the joint distribution of the study variables and their missingness indicators. These joint models cannot be estimated from the data alone, thus requiring the analyst to impose restrictions that make the models uniquely obtainable from the distribution of the observed data. We present an approach for constructing classes of identifiable nonignorable missing data models. The main idea is to use a sequence of carefully set up identifying assumptions, whereby we specify potentially different missingness mechanisms for different blocks of variables. We show that the procedure results in models with the desirable property of being non-parametric saturated. VL - 104 ER - TY - CHAP T1 - A Comparison of Blocking Methods for Record Linkage T2 - Privacy in Statistical Databases Y1 - 2014 A1 - Steorts, R. A1 - Ventura, S. A1 - Sadinle, M. A1 - Fienberg, S. E. A1 - Domingo-Ferrer, J. JF - Privacy in Statistical Databases PB - Springer VL - 8744 UR - http://link.springer.com/chapter/10.1007/978-3-319-11257-2_20 ER - TY - JOUR T1 - Detecting Duplicates in a Homicide Registry Using a Bayesian Partitioning Approach JF - Annals of Applied Statistics Y1 - 2014 A1 - Sadinle, M. VL - 8 ER - TY - JOUR T1 - A Generalized Fellegi-Sunter Framework for Multiple Record Linkage with Application to Homicide Record Systems JF - Journal of the American Statistical Association Y1 - 2013 A1 - Sadinle, M. A1 - Fienberg, S. E. VL - 108 UR - http://dx.doi.org/10.1080/01621459.2012.757231 ER - TY - CONF T1 - Approaches to Multiple Record Linkage T2 - Proceedings of the 58th World Statistical Congress Y1 - 2011 A1 - Sadinle, M. A1 - Hall, R. A1 - Fienberg, S. E. JF - Proceedings of the 58th World Statistical Congress PB - International Statistical Institute CY - Dublin UR - http://2011.isiproceedings.org/papers/450092.pdf ER -