Principles and Practice of Structural Equation Modeling (2nd ed.)

Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their relationships. A common goal of PLS-SEM analyses is to identify key success factors and sources of competitive advantage for important target constructs such as customer satisfaction, customer loyalty, behavioral intentions, and user behavior. Building on an introduction of the fundamentals of measurement and structural theory, this chapter explains how to specify and estimate path models using PLS-SEM. Complementing the introduction of the PLS-SEM method and the description of how to evaluate analysis results, the chapter also offers an overview of complementary analytical techniques. A PLS-SEM application of the widely recognized corporate reputation model illustrates the method.

Partial Least Squares Structural Equation Modeling

A comparative study of CB-SEM and PLS-SEM for theory development in family firm research

Correlation and causality

Choosing PLS path modeling as analytical method in European management research: A realist perspective

Structural equation modeling (SEM) is a versatile statistical modeling tool. Its estimation techniques, modeling capacities, and breadth of applications are expanding rapidly. This module introduces some common terminologies. General steps of SEM are discussed along with important considerations in each step. Simple examples are provided to illustrate some of the ideas for beginners. In addition, several popular specialized SEM software programs are briefly discussed with regard to their features and availability. The intent of this module is to focus on foundational issues to inform readers of the potentials as well as the limitations of SEM. Interested readers are encouraged to consult additional references for advanced model types and more application examples.

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Introduction to Structural Equation Modeling: Issues and Practical Considerations

The investigators used data from the Early Childhood Longitudinal Study—Kindergarten Cohort (ECLS-K) to estimate whether and to what extent the timing and persistence of mathematics difficulties (MD) in kindergarten predicted children's first through fifth grade math growth trajectories. Results indicated that children persistently displaying MD (i.e., those experiencing MD in both fall and spring of kindergarten) had the lowest subsequent growth rates, children with MD in spring only had the second-lowest growth rates, and children with MD in the fall only (and who had thus recovered from their MD by the spring of kindergarten) had the next-lowest growth rates. The children who did not have MD in either fall or spring of kindergarten had the highest growth rates. These results were observed prior to and after statistical control for additional variables. They indicate that measuring the timing and persistence of kindergarten children's mathematics learning difficulties may help identify those most at ris...

Five-Year Growth Trajectories of Kindergarten Children With Learning Difficulties in Mathematics:

The authors used a large sample of children (N ≈ 7,400) participating in the Early Childhood Longitudinal Study–Kindergarten Cohort (ECLS-K) to estimate kindergarten children’s academic achievement growth trajectories in reading and mathematics. The authors were particularly interested in whether the growth trajectories of children with learning disabilities (LD) or speech language impairments (SLI)—as well as those of other groups of children—were consistent with a cumulative or compensatory developmental cycle. Both LD and SLI children displayed significantly lower levels of kindergarten reading achievement than nondisabled children. However, and over the subsequent 5 years of elementary school, only children with SLI lagged increasingly behind nondisabled peers in their reading skills growth. The authors observed a different pattern for mathematics achievement. Children with LD, but not SLI, lagged increasingly behind nondisabled children in their mathematics skills growth. The authors also observed so...

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Kindergarten Children’s Growth Trajectories in Reading and Mathematics Who Falls Increasingly Behind?

Estimation in structural equation modeling.

This study evaluated the extent to which a range of risk factors (e.g., gender, race/ethnicity, low socioeconomic status) predicted kindergarten children's likelihood of later displaying recurring psychopathology. It used multilevel logistic regression to analyze teacher ratings of frequent and recurring externalizing and internalizing problem behaviors in a longitudinal sample of 4,674 children participating in the Early Childhood Longitudinal Study—Kindergarten Cohort, 1998—1999. Results indicated that those most at risk of displaying externalizing problem behaviors in both the third and fifth grade are those entering school already displaying high levels of these behaviors, as well as those displaying low reading readiness. Hispanics are at reduced risk of such problem behaviors. Those most at risk of displaying internalizing behavior problems in the third and fifth grades are those entering kindergarten with such problems and those displaying inattention and other learning-related behavior problems. Asian children are at reduced risk of recurring internalizing behavior problems. Females and children from higher SES families are at reduced risk for both types of psychopathology.

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Qiong Wu

Papers

Introduction to Structural Equation Modeling: Issues and Practical Considerations

Five-Year Growth Trajectories of Kindergarten Children With Learning Difficulties in Mathematics:

Kindergarten Children’s Growth Trajectories in Reading and Mathematics Who Falls Increasingly Behind?

Estimation in structural equation modeling.

Kindergarten Predictors of Recurring Externalizing and Internalizing Psychopathology in the Third and Fifth Grades