Handbook of Missing Data Methodology

By Geert Molenberghs, Garrett M. Fitzmaurice, Michael G. Kenward, Anastasios A. Tsiatis, Geert Verbeke. 2019

290 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ad2f23ebbd072af02d973bf8d7b01c8cd2d4addc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Manuela González‐Suárez
2. T. F. Johnson
3. Nick J B Isaac
4. Agustín Paviolo

In Statistics and Probability

1. Manuela González‐Suárez
2. T. F. Johnson
3. Nick J B Isaac
4. Agustín Paviolo

Citations in the corpus

• Handling missing values in trait data (2020, methodology): “However, there are imputation options, beyond the scope of the present study, designed specifically for severely biased MNAR data (Molenberghs et al., 2015).”