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What is Two-Level Multilevel Model

Handbook of Research on Organizational Transformations through Big Data Analytics
Refers to analytic methods for data with two levels where individuals (micro-level) are nested within organizational groups (macro-level) and there are independent variables (predictors) characterizing each of the two levels of the multilevel model.
Published in Chapter:
Predictive Analytics
Sema A. Kalaian (Eastern Michigan University, USA) and Rafa M. Kasim (Indiana Tech University, USA)
DOI: 10.4018/978-1-4666-7272-7.ch002
Abstract
Predictive analytics and modeling are analytical tools for knowledge discovery through examining and capturing the complex relationships and patterns among the variables in the existing data in efforts to predict the future organizational performances. Their uses become more common place due largely to collecting massive amount of data, which is referred to as “big data,” and the increased need to transform large amounts of data into intelligent information (knowledge) such as trends, patterns, and relationships. The intelligent information can then be used to make smart and informed data-based decisions and predictions using various methods of predictive analytics. The main purpose of this chapter is to present a conceptual and practical overview of some of the basic and advanced analytical tools of predictive analytics. The chapter provides a detailed coverage of some of the predictive analytics tools such as Simple and Multiple-Regression, Polynomial Regression, Logistic Regression, Discriminant Analysis, and Multilevel Modeling.
Full Text Chapter Download: US $37.50 Add to Cart
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Multilevel Modeling Methods for E-Collaboration Data
Refers to analytic methods for data with two levels where individuals are nested within e-collaboration groups and there are predictors characterizing individuals as well as groups.
Full Text Chapter Download: US $37.50 Add to Cart
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