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Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EPPS 7318 (Overall) | |||||
A | |||||
EPPS 7318 Harold Clarke | |||||
A | |||||
EPPS 7318 Karl Ho | |||||
A | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EPPS 7318 (Overall) | |||||
A | |||||
EPPS 7318 Harold Clarke | |||||
A | |||||
EPPS 7318 Karl Ho | |||||
A | |||||
Structural Equation and Multilevel (Hierarchical) Modeling
EPPS 7318
School of Economic, Political and Policy Sciences
An introduction to structural equation modeling (SEM) and multilevel modeling (MLM), sometimes called hierarchical linear or mixed modeling. SEM represents a general approach to the statistical examination of the fit of a theoretical model to empirical data. Topics include observed variable (path) analysis, latent variable models (e.g., confirmatory factor analysis), and latent variable SEM analyses. MLM represents a general approach to handling data that are nested within each other or have random components. Topics include dealing with two-level data that may be cross-sectional, such as students within classes, or longitudinal, such as repeated observations on individuals, firms or countries. Recommended Prerequisite: Students should have taken an introductory statistics or econometrics course. 3 credit hours.
Offering Frequency: Every two years
Grades: 46
Median GPA: A
Mean GPA: 3.930
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Structural Equation and Multilevel (Hierarchical) Modeling
EPPS 7318
School of Economic, Political and Policy Sciences
An introduction to structural equation modeling (SEM) and multilevel modeling (MLM), sometimes called hierarchical linear or mixed modeling. SEM represents a general approach to the statistical examination of the fit of a theoretical model to empirical data. Topics include observed variable (path) analysis, latent variable models (e.g., confirmatory factor analysis), and latent variable SEM analyses. MLM represents a general approach to handling data that are nested within each other or have random components. Topics include dealing with two-level data that may be cross-sectional, such as students within classes, or longitudinal, such as repeated observations on individuals, firms or countries. Recommended Prerequisite: Students should have taken an introductory statistics or econometrics course. 3 credit hours.
Offering Frequency: Every two years
Grades: 46
Median GPA: A
Mean GPA: 3.930
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