Multivariate Analysis

Authors
Affiliations

Doctor of Physical Therapy

B.S. in Kinesiology

Doctor of Physical Therapy

B.A. in Neuroscience

My first attempt at multivariate analysis was during a research project aimed to determine what factors predict whether a physical therapy patient will I initially ran a univariate analysis then only included significant univariate predictors in the final multivariate analysis.

Determine the type of multivariate analysis

layout ### Multivariate Analysis of Variance (MANOVA): “Used when there are multiple dependent variables and the predictors are categorical. Tests whether the means of multiple dependent variables differ across groups.”

Principal Component Analysis (PCA):

“A dimensionality reduction technique. Focuses on finding patterns in data and reducing its complexity, not prediction.”

Structural Equation Modeling (SEM):

“Models complex relationships between multiple dependent and independent variables, including latent variables. Combines aspects of factor analysis and regression.”

Cluster Analysis:

“Groups observations based on similarity without specifying dependent variables. Used in exploratory data analysis.”

Mixed-Effects Models:

“Extends GLMs to include both fixed and random effects. Often used for hierarchical or grouped data.”

Canonical Correlation Analysis (CCA):

“Examines the relationships between two sets of variables. Discriminant Analysis:

Predicts group membership based on predictor variables (used for classification).”

Survival Analysis:

Models time-to-event data. May use extensions like Cox proportional hazards, which are not always GLMs.

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