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Journal Issue
Volume 12 Issue 1 / Jul 2014  pp1‑74

Editor: Ann Brown

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Editorial for General Issue  pp1‑2

Ann Brown

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Multicollinearity in Marketing Models: Notes on the Application of Ridge Trace Estimation in Structural Equation Modelling  pp3‑15

Jenni Niemelä-Nyrhinen, Esko Leskinen

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The Impact of non‑Equidistance on Anova and Alternative Methods  pp16‑26

Bjorn Lantz

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SEM for Experimental Designs: An Information Systems Example  pp27‑40

Saurabh Gupta

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Abstract

Abstract: IS research has matured significantly over the last three decades, leading to increasingly complex research designs as well as complex analytical techniques to analyze the data collected. Similar advances have happened in the experimental and qu asi‑experimental designs. Some key characteristics of these advances are: 1) use of latent variables approaches to operationalize key variables; 2) the need to understand the causal relationship between elements of the study; 3) the need to study the e ffects of technology as an addition to existing methods of working; and, 4) recognition that some conditions create greater change in outcomes over time. In spite of these advances in data collection and design, researchers are still confirming data coll ected via experiments to use ANOVA for analysis. This paper outlines an analytical technique that moves Information Systems experimental research beyond ANOVA. By combining and extending three advances in Structural Equation Modeling techniques, namely Me an and Covariance Structure analysis, Stacked Group modeling and Latent Growth modeling, the paper outlines a robust analysis technique that accommodates the above‑mentioned advances in experimental design. The technique provides for an in‑depth test of a ll model assumptions, as well as the flexibility to accommodate an increasing variety of experimental designs. A detailed example is provided to illustrate the usage of the technique in an Information Systems context. The example shows now only the accomm odations needed in an information systems context, but also how this technique can be used to extract results from existing research methods that was not possible with ANOVA. The arguments presented in the paper as well as the example on how to use should provide future researchers with a guideline on how to use these techniques as well as provide a platform for how they can extend these techniques to accommodate more research method advances. 

 

Keywords: Keywords: SEM, experiments, stacked group modeling, latent growth modeling, invariance, Information Systems

 

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Surveying Adolescents: The Impact of Data Collection Methodology on Response Quality  pp41‑53

Beverly Wright, Alphonso O. Ogbuehi

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Using the Multiple Case Study Design to Decipher Contextual Leadership Behaviors in Indian Organizations  pp54‑65

Veena Vohra

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Theory Testing Using Case Studies  pp66‑74

Ann-Kristina Løkke, Pernille Dissing Sørensen

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