PLS-based SEM Algorithms: The Good Neighbor Assumption, Collinearity, and Nonlinearity
نویسندگان
چکیده
منابع مشابه
Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach
We discuss common method bias in the context of structural equation modeling employing the partial least squares method (PLS-SEM). Two datasets were created through a Monte Carlo simulation to illustrate the discussion: one contaminated by common method bias, and the other not contaminated. A practical approach is presented for the identification of common method bias based on variance inflatio...
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An important source of bias in structural equation modeling (SEM) employing the partial least squares method (PLS) is missing data. Deletion methods, such as listwise and pairwise deletion, have traditionally been used to deal with missing data. These methods are perceived as leading to selective loss of data and significant related biases. Missing data imputation methods, on the other hand, do...
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The prevalence of obesity is rising globally, and the United States has one of the highest obesity rates in the world: ≈17% of the young and >33% of adults are obese. Obesity is associated with chronic low-grade systemic inflammation, which is considered a critical underlying factor in the development of insulin resistance (IR). IR is a major risk factor for type 2 diabetes mellitus (T2DM) and ...
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Research Practice Ned Kock Texas A&M International University [email protected] Gary S. Lynn Stevens Institute of Technology [email protected] Variance-based structural equation modeling is extensively used in information systems research, and many related findings may have been distorted by hidden collinearity. This is a problem that may extend to multivariate analyses, in general, in the fiel...
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ژورنال
عنوان ژورنال: Information Management and Business Review
سال: 2015
ISSN: 2220-3796
DOI: 10.22610/imbr.v7i2.1146