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Developing Multilevel Models for Research

Developing Multilevel Models for Research
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Author(s): John Turner (University of North Texas, USA), Kristin Firmery Petrunin (University of North Texas, USA) and Jeff Allen (University of North Texas, USA)
Copyright: 2015
Pages: 27
Source title: Handbook of Research on Scholarly Publishing and Research Methods
Source Author(s)/Editor(s): Victor X. Wang (Florida Atlantic University, USA)
DOI: 10.4018/978-1-4666-7409-7.ch023

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Abstract

In the past, a large number of research efforts concentrated on single-level analysis; however, researchers who only conduct this level of analysis are finding it harder to justify due to the advancements in statistical software and research techniques. The validation of research findings comes partially from others replicating existing studies as well as building onto theories. Through replication and validation, the research process becomes cyclical in nature, and each iteration builds upon the next. Each succession of tests sets new boundaries, further verification, or falsification. For a model to be correctly specified, the level of analysis needs to be in congruence with the level of measurement. This chapter provides an overview of multilevel modeling for researchers and provides guides for the development and investigation of these models.

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