Performance of Imputation Algorithms on Artificially Produced Missing at Random Data

Performance of Imputation Algorithms on Artificially Produced Missing at Random Data

Missing data is one of the challenges we are facing today in modeling valid statistical models. It reduces the representativeness of the data samples. Hence, population estimates, and model parameters estimated from such data are likely to be biased. However, the missing data problem is an area unde...

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Bibliographic Details
Main Author: Oketch, Tobias O
Format: Others
Language:English
Published: Digital Commons @ East Tennessee State University 2017
Subjects:
Missing not at random
Missing completely at random
Missing at random
Multiple imputation
Multiple imputation by chained equation
Relative efficiency.
Applied Statistics
Multivariate Analysis
Statistical Models
Online Access:https://dc.etsu.edu/etd/3217
https://dc.etsu.edu/cgi/viewcontent.cgi?article=4633&context=etd

Internet

https://dc.etsu.edu/etd/3217
https://dc.etsu.edu/cgi/viewcontent.cgi?article=4633&context=etd

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