[图书][B] Applied multiple imputation
K Kleinke, J Reinecke, D Salfrán, M Spiess - 2020 - Springer
… us that they have read about multiple imputation (MI) but that … understanding of the theory
of multiple imputation, that is, what … behind the method of multiple imputation are explained in …
of multiple imputation, that is, what … behind the method of multiple imputation are explained in …
Multiple imputation of multiple multi-item scales when a full imputation model is infeasible
… In these data, applying multiple imputation by chained equations to the individual scale …
We propose an adaptation of multiple imputation by chained equations which imputes the …
We propose an adaptation of multiple imputation by chained equations which imputes the …
Multiple imputation with missing data indicators
… For comparison, we evaluate the performance of the various SRMI adaptations to imputation
using the “exact” imputation model in equation (2). This distribution may only be known up …
using the “exact” imputation model in equation (2). This distribution may only be known up …
Multiple imputation
DB Rubin - Flexible imputation of missing data, Second edition, 2018 - taylorfrancis.com
… imputed values could not be calculated with certainty. His solution was simple and brilliant:
create multiple imputations … the models and how to derive the imputations. A low number of …
create multiple imputations … the models and how to derive the imputations. A low number of …
Multiple imputation of missing data in multilevel designs: A comparison of different strategies.
O Lüdtke, A Robitzsch, S Grund - Psychological methods, 2017 - psycnet.apa.org
… Multiple imputation is a widely recommended means of … that the imputation model used to
generate the imputed values … be taken into account in the imputation model. In the present …
generate the imputed values … be taken into account in the imputation model. In the present …
[图书][B] Multiple imputation of missing data in practice: Basic theory and analysis strategies
Y He, G Zhang, CH Hsu - 2021 - taylorfrancis.com
… handling missing data using multiple imputation after reading this book! We also hope some
of the material can motivate readers to develop new multiple imputation ideas and methods. …
of the material can motivate readers to develop new multiple imputation ideas and methods. …
Integration of Multikinds Imputation With Covariance Adaptation Based on Evidence Theory
… of imputation methods to obtain multiple imputed training datasets. In general, the distributions
of each imputed … A covariance adaptation module (CAM) is then developed to reduce the …
of each imputed … A covariance adaptation module (CAM) is then developed to reduce the …
Should multiple imputation be the method of choice for handling missing data in randomized trials?
TR Sullivan, IR White, AB Salter… - Statistical methods in …, 2018 - journals.sagepub.com
… Based on these results, we conclude that multiple imputation should not be seen as the only
… In settings where multiple imputation is adopted, we recommend that imputation is carried …
… In settings where multiple imputation is adopted, we recommend that imputation is carried …
Handling missing data: analysis of a challenging data set using multiple imputation
M Pampaka, G Hutcheson… - International Journal of …, 2016 - Taylor & Francis
… Whilst data imputation (particularly multiple imputation (MI)) is now generally accepted by
statisticians, non-specialist researchers have been slow to adopt it. Data imputation makes an …
statisticians, non-specialist researchers have been slow to adopt it. Data imputation makes an …
Multiple imputation of multilevel missing data: an introduction to the R package pan
S Grund, O Lüdtke, A Robitzsch - Sage Open, 2016 - journals.sagepub.com
… state-of-the-art procedures such as multiple imputation (MI) may require advanced statistical
… several tools for managing and analyzing multiply imputed data sets. We illustrate the use of …
… several tools for managing and analyzing multiply imputed data sets. We illustrate the use of …
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