Missing-data-analysis-Review-Articles | 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. Review article comes in the form of systematic reviews and literature reviews and are a form of secondary literature. Systematic reviews determine an objective list of criteria, and find all previously published original research papers that meet the criteria. They then compare the results presented in these papers. Literature reviews, by contrast, provide a summary of what the authors believe are the best and most relevant prior publications. The concept of "review article" is separate from the concept of peer-reviewed literature. It is possible for a review to be peer-reviewed, and it is possible for a review to be non-peer-reviewed.
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Last date updated on March, 2021