@article{hip16num,
  archivePrefix = {arXiv},
  eprinttype = {arxiv},
  eprint = {1608.05406},
  title = {The Number of Imputations Should Increase Quadratically with the Fraction of Missing Information},
  abstract = {Users of multiple imputation often want to know how many imputations they need. An old answer is that 3 to 10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. If users also want replicable standard errors, users often need more imputations. A popular rule is that the required number of imputations increases linearly with the fraction of missing information, but we show that, in fact, the number of imputations increases quadratically with the fraction of missing information. This quadratic relationship implies that users should add imputations until the degrees of freedom in the standard errors exceeds some threshold (e.g., 200). We suggest a two-step procedure in which the user conducts a pilot analysis using a small number of imputations and then uses the results to calculate the number of imputations that are needed for a final analysis to have the desired degrees of freedom.},
  author = {{von Hippel}, Paul T.},
  month = aug,
  year = {2016},
  keywords = {missing-data,multiple-imputation},
  citeulike-article-id = {14314910},
  citeulike-attachment-1 = {hip16num.pdf; /pdf/user/harrelfe/article/14314910/1105156/hip16num.pdf; 7e463a20e640452205c2d55ceb271213ef8fe059},
  citeulike-linkout-0 = {http://arxiv.org/abs/1608.05406},
  citeulike-linkout-1 = {http://arxiv.org/pdf/1608.05406},
  day = {17},
  posted-at = {2017-03-20 20:44:10},
  priority = {0}
}

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