Statistical approaches for handling longitudinal and cross sectional discrete data with missing values focusing on multiple imputation and probability weighting.
dc.contributor.advisor | Mwambi, Henry Godwell. | |
dc.contributor.author | Stephen, Aluko Omololu. | |
dc.date.accessioned | 2019-06-05T13:16:45Z | |
dc.date.available | 2019-06-05T13:16:45Z | |
dc.date.created | 2018 | |
dc.date.issued | 2018 | |
dc.description | Doctor of Philosophy in Science. University of KwaZulu-Natal, Pietermaritzburg, 2018. | en_US |
dc.description.abstract | Abstract available in PDF file. | en_US |
dc.identifier.uri | https://researchspace.ukzn.ac.za/handle/10413/16318 | |
dc.language.iso | en | en_US |
dc.subject.other | Missing data. | en_US |
dc.subject.other | Longitudinal studies. | en_US |
dc.subject.other | Missing completely at random. | en_US |
dc.subject.other | Missing at random. | en_US |
dc.title | Statistical approaches for handling longitudinal and cross sectional discrete data with missing values focusing on multiple imputation and probability weighting. | en_US |
dc.type | Thesis | en_US |
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