Missing-data-analysis-Innovations
Missing data analysis is omnipresent in research in social sciences. At the research design stage, it's important to consider the issues raised by missing data. Since unplanned missing data inevitably introduces ambiguity in the inferences that can be derived from a study , the design should be scrutinized carefully to minimize the scope for missing data rise. Considerable treatment will pay a significant dividend over this dimension of design when the study is evaluated. Innovation can be seen as implementing improved approaches that satisfy existing needs, unarticulated needs or
business needs. It is proficient by making more competitive goods, systems, services, technology, or innovative concepts readily accessible to consumers, governments, and society. Innovations are an original and novel thing, as a significant new thing that "breaks into" the market or society. In almost all serious statistical analyses, missing data emerge.
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