Missing Values: What is Really Missing with Missing Values


WHEN June 23, 2021
3-4:30 PM WHERE Zoom Webinar WHO Statistical Consulting Laboratory (StatsLab) Open to the Public

In the talk,  Christian Heumann  will first try to motivate why simply ignoring the problem of missing data is a bad option if a substantial amount of data is missing. Imputation has been proposed a long time ago as a method to treat the problem of missing data adequately. Since single imputation has also severe disadvantages, the standard is (or should be) nowadays multiple imputations. Here, several options can be chosen by the imputer. Finally, Heumann will discuss how to bootstrap and multiple imputations can be combined for inference purposes, e.g. standard errors or confidence intervals. 

Email nyuad.statslab@nyu.edu for more details.

  • Christian Heumann, Professor, Department of Statistics, Ludwig-Maximilians-Universität München
Hosted by
  • Statistical Consulting Laboratory (StatsLab)

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