Missing-data-analysis-Online-Journals | Journal Of Biometrics And Biostatistics

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Missing data arise in almost all serious statistical analyses. Missing data are ubiquitous in social science research. It is important to consider the issues raised by missing data at the research design stage. As unplanned missing data inevitably introduce ambiguity into the inferences that can be drawn from a study, the design should be carefully scrutinised to minimise the scope for missing data to arise. Considerable care over this aspect of design will pay a substantial dividend when the study is analysed. Inevitably, however, missing data will arise. Ambiguity in the analysis can be reduced if the chance of the data being missing depends only on observed data; the so-called ‘missing at random’ scenario. Online Journals are scholarly and peer reviewed journals. The journals provide forum and motivates scientists, researchers, academics, engineers, and practitioners in all aspects to share their professional and academic knowledge in the fields computing, engineering, humanities, economics, social sciences, management, medical science, and related disciplines. Online Journals also aims to reach a large number of readers worldwide with original and current research work completed on the vital issues of the above important disciplines. The journals permit all readers to read, view, download and print the full-text of all published articles without any subscription or restrictions.
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Last date updated on June, 2021