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The Validation Process for Tier-III Variables and Fitness of the Model

The Validation Process for Tier-III Variables and Fitness of the Model

Copyright: © 2013 |Pages: 17
ISBN13: 9781466642010|ISBN10: 1466642017|EISBN13: 9781466642027
DOI: 10.4018/978-1-4666-4201-0.ch010
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MLA

Harekrishna Misra and Hakikur Rahman. "The Validation Process for Tier-III Variables and Fitness of the Model." Managing Enterprise Information Technology Acquisitions: Assessing Organizational Preparedness, IGI Global, 2013, pp.238-254. https://doi.org/10.4018/978-1-4666-4201-0.ch010

APA

H. Misra & H. Rahman (2013). The Validation Process for Tier-III Variables and Fitness of the Model. IGI Global. https://doi.org/10.4018/978-1-4666-4201-0.ch010

Chicago

Harekrishna Misra and Hakikur Rahman. "The Validation Process for Tier-III Variables and Fitness of the Model." In Managing Enterprise Information Technology Acquisitions: Assessing Organizational Preparedness. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-4201-0.ch010

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Abstract

The validation of the model is dependent on the strength of the relationships established through variables, and Tier-III influencers are designed to ensure the validation process at a macro level. Tier-III influencers of the model help us understand the relations between variables matching (fitting) the data (Tier-I and II) and the way they influence the appropriateness of the model. Tier-III influencers characterize theoretical testing of the model and are mostly based on theory-driven search for the important antecedents of one or more focal variables. Tier-III influencers help us understand the relationship among the variables governing the outcome of the proposed model. It is agreed that the process of testing or validating theoretical models with survey data is addressed by first determining the adequacy of the measures of the unobserved variables in the model and then determining the reasonableness or adequacy of the hypothesized model. Measurements of Tier-III use conceptual definitions of the unobserved or latent variables, along with observed variables or items that measure these unobserved or latent variables. This chapter discusses model-to-data fit and parameter estimates by utilizing structural equation analysis. Model adequacy is determined by using hypotheses and model-to-data fit and parameter estimates from structural models.

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