Share: Worm

have been doing this for ten years.  I admire you for retaining your…” he trailed off.


“Not a word I’m familiar with, Weaver.  Faith?”

“Faith works.”

“I have none left, after ten years.  No faith.  We are a wretched, petty species, and we have been given power to destroy ourselves with

Factor Analysis — notes

Factor Analysis:

Multiple Classifications:

Aka [Dimensionality reduction](
[Dimensionality Estimation] (
###  Methods:
    * [Intrinsic Dimension Estimation](
      or (
    * [PCA](
    * [Kernel-PCA](
    * [Graph-based kernel PCA](
    * [Linear Discriminant Analysis](
    * [Generalized Discriminant Analysis](
    * [Manifold Learning] (
### Factor Analysis(based on goal):

    *  [Exploratory Factor
        #### Fitting Procedures:
            * used to estimate factor loadings and unique variances

    * [Confirmatory Factor

### Types of factoring:
    * [Principal Component

    * Canonical Factor Analysis: aka Rao's canonical factoring, uses principal axis
      method, unaffected by arbitrary rescaling, highest canonical correlation measure.

    * Common Factor Analysis: aka principal factor analysis, least no. of variables
      accounting for the common variance of a set of variables.

    * Image Factoring: based on correlation matrix of predicted variables, where each
      prediction is done via [multiple

    * Alpha Factoring: based on maximizing reliability of factors, assumes random
      sampling of variables from universe of vars, (other methods assume fixed

    * Factor Regression Model: Combinatorial model of factor and regression models,
        aka hybrid factor model with partially known factors

### Terminology:
    * Factor Loadings:
    * Interpreting Factor loadings:
    * Communality:
    * Spurious Solutions:
    * Uniqueness of Variable:
    * EigenValues/Characteristic Roots:
    * Extraction Sums of squared loadings:
    * Factor Scores:

### Criteria for number of Factors:
    * Horn's Parallel Analysis:
    * Velicer's MAP test:
     older methods
    * Kaiser Criterion:
    * Scree plot:
    * Variance explained criteria:

### Rotation Methods:
    * Varimax Rotation:
    * Quartimax Rotation:
    * Equimax Rotation:
    * Direct oblimin Rotation:
    * Promax Rotation: