Factor Analysis

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Factor Analysis

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Find underlying attributes that influence choice. Advertising research/media usage ... Break (elbow) in scree plot. Percent variance explained. Should be at least 60 ... – PowerPoint PPT presentation

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Title: Factor Analysis


1
Factor Analysis
2
Grouping Variables into Constructs
3
Purpose
  • Data reduction
  • If high redundancy in measures
  • If construct measures require multiple items
    (e.g., store image)
  • Substantive interpretation

4
Marketing Applications
  • Market segmentation
  • Find underlying variables to group consumers
  • Product research
  • Find underlying attributes that influence choice
  • Advertising research/media usage
  • Pricing studies
  • Find characteristics of price-sensitive consumers

5
Background
  • No (in)dependent variables
  • Metric inputs and outputs
  • Operates on correlation matrix, so assumes
    variables related linearly
  • Assumes variables sufficiently intercorrelated
  • Sphericity and KMO tests

6
When Factor Analysis Will Be Beneficial
7
When Factor Analysis Will Not be Beneficial
8
Key Definitions
  • Factor
  • Linear combination of variables (derived
    variable)
  • Underlying dimension that explains correlations
    among set of variables
  • Factor score
  • Each subjects score on derived variable
  • Used in subsequent analysis

9
Key Definitions (cont.)
  • Factor loadings
  • Correlation between factors and original variable
    (if standardized)
  • All original variables with high loading (near
    1.0 on same factor grouped together
  • Communality
  • Percent of variation in an original variable
    explained by all the factors used

10
Key Definitions (cont.)
  • Explained variance
  • Percent of variation in all the data explained by
    each factor (eigenvalue)

11
Stopping Rules
  • A priori determination
  • Eigenvalue gt 1.0
  • Break (elbow) in scree plot
  • Percent variance explained
  • Should be at least 60
  • Split data, run both halves, and compare
  • Test statistical significance of eigenvalues
  • Problem With ngt200, many minor factors will seem
    significant

12
Improve Interpretation by Rotating Factors
  • Orthogonal
  • Varimax (maximum 1 and 0s)
  • Oblique
  • Regardless, factor names are subjective

13
Steps in Conducting a Factor Analysis
14
Example 1 Item Set
15
Results Example 1
16
Factor 1
Example 2 Factor Loadings for Attitudes toward
Discount Stores
Factor 2
Factor 3
Factor 4
Factor 5
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