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Direct linkRoy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
Wes Bonifay; Li Cai; Carl F. Falk; Kristopher J. Preacher – Grantee Submission, 2025
Model complexity is a critical consideration when evaluating a statistical model. To quantify complexity, one can examine fitting propensity (FP), or the ability of the model to fit well to diverse patterns of data. The scant foundational research on FP has focused primarily on proof of concept rather than practical application. To address this…
Descriptors: Statistical Analysis, Models, Goodness of Fit, Factor Analysis
Raghav Sandhane; Kanchan Patil; Shaji Joseph – Learning Organization, 2025
Purpose: In the present competing environment, it is essential to understand how some information technology (IT) organizations do well and outperform others. This paper aims to assess the impact of the learning disciplines proposed by Peter Senge (1990) on the performance of IT organizations. The study also aims to find the impact of…
Descriptors: Organizational Learning, Information Technology, Structural Equation Models, Performance
