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Replication Data for: Listwise Deletion In High Dimensions

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication Data for: Listwise Deletion In High Dimensions
 
Identifier https://doi.org/10.7910/DVN/T8BG2K
 
Creator Wang, J. Sophia
Peter M. Aronow
 
Publisher Harvard Dataverse
 
Description We consider the properties of listwise deletion when both n and the number of variables grow large. We show that when (i) all data has some idiosyncratic missingness and (ii) the number of variables grows superlogarithmically in n, then, for large n, listwise deletion will drop all rows with probability 1. Using two canonical datasets from the study of comparative politics and international relations, we provide numerical illustration that these problems may emerge in real world settings. These results suggest, in practice, using listwise deletion may mean using few of the variables available to the researcher.
 
Subject Social Sciences
 
Contributor Wang, J. Sophia