Eigenmode Method for Psychotherapeutic Research
What is an Eigenmode?
Introduction
An eigenmode of a system shows the hidden themes in messy data. When you measure lots of things at once (survey items, test scores, brain channels), many of them are secretly related. Eigenmode analysis surfaces those groupings automatically.An eigenmode is an underlying pattern obtained by linearly decomposing a dataset into orthogonal (uncorrelated) components, each capturing an independent axis of covariation, ordered by how much of the variance it explains.
Jupyter Notebook Walkthrough
This video provides a brief walkthrough of the code and techniques included in the Eigenmodality Jupyter Notebook.
Eigenmodality Use Case Example
CC 4.0
Example Dataset
We'll use an existing dataset as an example of how this proposed analysis pipeline works.
The data set is from a study on positive psychology that offered one of four techniques found within positive psychology to the 202 subjects. Happiness (AHI) and depressions (CESD) scores before and after the intervention were collected. For PCA analysis I extracted these two testing occasions, splitting the column of each score into pre and post scores so that the timing would be included in the PCA.
J. Woodworth, Rosalind; O'Brien-Malone, Angela; Diamond, Mark R.; Schüz, Benjamin (2018). A randomized placebo-controlled trial of positive psychology interventions in Australia. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1577563.v1
Analysis Methodology
Pipeline Tutorial
Log & Robust Scaling
Preliminary AnalysisPrincipal Component Analysis (PCA)
ClusteringModeling
Resources
Documents
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