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The case for the use of multiple imputation missing data methods in stochastic frontier analysis with illustration using English local highway data

Stead, Alexander D.; Wheat, Phill - In: European journal of operational research : EJOR 280 (2020) 1, pp. 59-77

Persistent link: https://www.econbiz.de/10012132361

Multiple imputation strategies for zero-inflated cost data in economic evaluations : which method works best?

MacNeil Vroomen, Janet; Eekhout, Iris; Dijkgraaf, Marcel G. - In: The European journal of health economics : HEPAC ; … 17 (2016) 8, pp. 939-950

Persistent link: https://www.econbiz.de/10011660097

Multiple imputation : an attempt to retell the evolutionary process

Koller-Meinfelder, Florian - In: Wirtschafts- und sozialstatistisches Archiv : ASTA ; … 8 (2014) 4, pp. 249-267

Persistent link: https://www.econbiz.de/10010502059

Missing data : five practical guidelines

Newman, Daniel A. - In: Organizational research methods : ORM 17 (2014) 4, pp. 372-411

Persistent link: https://www.econbiz.de/10010418134

Hybrid multiple imputation in a large scale complex survey

Razzak, Humera; Heumann, Christian - In: Statistics in transition : an international journal of … 20 (2019) 4, pp. 33-58

Large-scale complex surveys typically contain a large number of variables measured on an even larger number of respondents. Missing data is a common problem in such surveys. Since usually most of the variables in a survey are categorical, multiple imputation requires robust methods for modelling...

Persistent link: https://www.econbiz.de/10012158128