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TOPIC
DESCRIPTION

Structural Equation Modeling (SEM)

A complex statistical technique used to model complex relationships among variables.

Multidimensional Scaling (MDS)

Involves representing data in a lower-dimensional space while preserving the original distances between data points.

Cluster Analysis

Involves grouping similar objects or individuals into clusters based on their characteristics.

Canonical Correlation Analysis (CCA)

Used to explore the relationships between two sets of variables.

Discriminant Analysis

Used for classification and predictive modeling.

Principal Component Analysis (PCA)

A widely used dimensionality reduction technique.

Factor Analysis

Used to uncover underlying factors that explain the patterns in data.

Multivariate Analysis of Variance (MANOVA)

An extension of ANOVA to multiple dependent variables.

Repeated Measures Analysis

Involves analyzing data collected from the same subjects over multiple time points.

Structural Equation Modeling (SEM)

A powerful technique that involves both measurement models and structural models.

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