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Measuring income inequality using survey data : the case of China
Chen, Yongwei; Fu, Dahai - In: Journal of economic inequality 13 (2015) 2, pp. 299-307
Persistent link: https://www.econbiz.de/10011327461
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Global environmental emissions estimate : application of multiple imputation
Miyama, Eriko; Managi, Shunsuke - In: Environmental economics and policy studies 16 (2014) 2, pp. 115-135
Persistent link: https://www.econbiz.de/10010351424
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Addressing missing data in patient-reported outcome measures (PROMS) : implications for the Use of PROMS for comparing provider performance
Gomes, Manuel; Gutacker, Nils; Bojke, Chris; Street, Andrew - In: Health economics 25 (2016) 5, pp. 515-528
Persistent link: https://www.econbiz.de/10011541858
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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
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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
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Direct payments, cash rents, land values, and the effects of imputation in US farm-level data
Robbins, Michael W.; White, T. Kirk - In: Agricultural and resource economics review : ARER 43 (2014) 3, pp. 451-470
Persistent link: https://www.econbiz.de/10011450916
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Is the whole larger than the sum of its parts? : impact of missing data imputation in economic evaluation conducted alongside randomized controlled trials
Michalowsky, Bernhard; Hoffmann, Wolfgang; Kennedy, Kevin; … - In: The European journal of health economics : HEPAC ; … 21 (2020) 5, pp. 717-728
Persistent link: https://www.econbiz.de/10012422019
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Multiple imputation of missing data for multilevel models : simulations and recommendations
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander - In: Organizational research methods : ORM 21 (2018) 1, pp. 111-149
Persistent link: https://www.econbiz.de/10011880091
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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
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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