The Effect of Varying Degrees of Nonnormality in Structural Equation Modeling

By Mingzhi Lei, Richard G. Lomax. 2005

753 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/dbda1417b7003dfc68b7c586b19ac36d495347d4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Information Systems

In Management Science and Operations Research

Citations in the corpus

Integration of Financial and Management Accounting Systems: The Mediating Influence of a Consistent Financial Language on Controllership Effectiveness (2011, methodology): “Although this method requires multivariate normality of data (Byrne, 2009), several simulation studies (e.g., Lei and Lomax, 2005; Boomsma and Hoogland, 2001) have shown that it is apparently quite robust against the violation of the normality assumption, leading to only marginally biased parameter…”
Use of structural equation modeling in operations management research: Looking back and forward ☆ (2006, methodology): “, 1992), although these effects are lessened with larger sample sizes (Lei and Lomax, 2005).”
Boredom in achievement settings: Exploring control–value antecedents and performance outcomes of a neglected emotion. (2010, background): “Given that the chi-square statistic is sensitive to sample sizes greater than 100 (e.g., Lei & Lomax, 2005), the nonsignificance of this statistic is especially impressive and implies that the model represents the data very well.”
Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach (2007, methodology): “Although our SEM still deviates from the multivariate normality assumption, the influence of non-normal data is reduced when using MLE with a larger sample size (Anderson and Amemiya 1988; Lei and Lomax 2005).”
The Curvilinear Relationship between Work Passion and Organizational Citizenship Behavior (2014, neutral): “The skewness for OCB is only .41, which is below the recommended threshold of 1.00 for the distribution to be considered approximately normal (Lei and Lomax 2005).”
On the Relation of Job Insecurity, Job Autonomy, Innovative Work Behaviour and the Mediating Effect of Work Engagement (2014, neutral): “Yet, building on the results of Lei and Lomax (2005), we should not be too concerned with the bias of the estimates in SEM modelling with non-normal variables.”
Nonnormality of Data in Structural Equation Models (2008, background): “Lei and Lomax tested the impacts of nonnormality with six combinations of univariate skewness (0 skewness 1.74) and kurtosis (0 kurtosis 3.8) for a model with six variables (16).”
On the Validity and Utility of Discriminating Among Impulsivity-Like Traits (2007, background): “Lei and Lomax (2005) reported that, for maximum likelihood analyses with sample sizes smaller than this one, under conditions of extreme skew and extreme kurtosis, parameter estimates tend to be biased by less than 1%.”
Digital support for student engagement in blended learning based on self-determination theory (2021, background): “All of the variables were internally reliable, as all of the α values ranged from 0.93 to 0.97 (where good > 0.80) and had sufficiently normal distributions (i.e., skewness less than 2.3, Lei & Lomax, 2005; kurtosis less than 7.0, Byrne, 2010).”
Impact of the Interactive Learning Environments in Children’s Prosocial Behavior (2018, background): “3 indicate a large divergence from the normal distribution [38].”
Key drivers of university‐industry relationships: the role of organisational compatibility and personal experience (2007, background): “219 respectively suggested slight to moderate univariate non-normality ( Lei and Lomax, 2005”
Non-normality of Data in Structural Equation Models (2008, background): “where CBGJobAccessibilitym is the job accessibility in census block groups m; nm is the number of traffic analysis zones (TAZs) contained in census block groups (CBG) m (TAZi ⊂CBGm); Jobi is the number of jobs in TAZ i, and TravelTimeij is the travel time from TAZ i to j in the three-hour AM peak pe”
Effects of brand personality, self-congruity and functional congruity on hotel brand loyalty (2019, methodology): “By the way, Levy (1959) highlighted symbolic consumption as a new perspective in explaining consumption behavior which argued that products are mostly purchased because of their symbolic meanings instead of the functional attributes.”