Factor Analysis

Exploratory and Confirmatory

If you have read my other post, I’m all about Farmer’s Talk. Perhaps it’s the innate tendency of me as a DC residence, but I despise acronyms if I can help it. Moreover, I am technically part of the Gen Y crowd, yet I can’t see myself talking in letters which makes no sense never mind bear any cultural distinction of one’s language.

But I digress…


In short, Factor Analysis is a way to find some form of relationships (or lack thereof) between variables (wiki’s version). There are two types:

  • Exploratory: Find the factors.
  • Confirmatory: Confirm the factors you find in Exploratory (aka EFA from the cool kidz) is legit.

By way of Factor Analysis Introduction

Another good introduction from Univ. of Hawaii


I’m sure there are tons more reason to do factor analysis than what I bullet below, but here are my experience thus far with Factor Analysis:

  • Determine groupings (err.. Factors, Categories, etc.) of variables for segmentation purposes.
  • Identify redundant variables for ease modeling by using subset of variables, thereby minimize run-time and/or ‘understanding-of-what-the-heck-you-are-looking-at’ time


In (our beloved, ‘high barrier to entry’) SAS:


  • Proc FACTOR


  • Proc CALIS

In (people’s republic of) R:

Exploratory: <to be written>

Confirmatory: <to be written>

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