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st: RE: Factor Analysis


From   "Nick Cox" <[email protected]>
To   <[email protected]>
Subject   st: RE: Factor Analysis
Date   Mon, 29 Sep 2003 10:25:44 +0100

hscheng and Li-Lang Yang both wrote 

> I am using the Stata commands -factor- (factor analysis) 
> and -score- (to
> create scores for different factors) for my study.  I have 
> 12 items and
> the factor analysis results show 4 different factors.  I 
> can generate
> scores for the 4 different factors in 2 different ways.  First,
> 
> . factor item1-item12  
> . score f1 f2 f3 f4  // so basically, do all of these at once
> 
> Second,
> 
> . factor item1-item12  //say, item1-3 for F1; item4-6 for F2, etc
> . factor item1-item3 
> . score f1 		// This generates the score for Factor 1
> . factor item4-item6 
> . score f2 		// This generates the score for Factor 2
> . factor item7-item9 
> . score f3 		// This generates the score for Factor 3
> . factor item10-item12 
> . score f4 		// This generates the score for Factor 4
> 
> I know the Stata menu uses the first way, but is the second 
> way wrong?
> The first way and the second way give different results.  
> Which one is
> more accurate?
> 

These commands produce completely different results 
in general, as they refer to different models. Accuracy 
is not an issue. 

First, note that -score- always picks up on the 
last -factor- or -pca- performed. It has that much 
memory, and no more. 

Given 12 variables, -factor- produces a model 
with up to 12 factors. 

Evidently in your case the first 4 of those 
seem important and those can be put in variables -f1-f4- 
by a single command. However, your other 
commands refer to separate factor analyses. 
So for example 

. factor item1-item3 

carries out a factor analysis on just three 
variables and any -score- command following
refers to that analysis. 

Nick 
[email protected] 
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