# st: Problem in factor analysis & Cronbach's alpha

 From "Xu, Haiyong" To "'statalist@hsphsun2.harvard.edu'" Subject st: Problem in factor analysis & Cronbach's alpha Date Tue, 11 Aug 2009 11:10:00 -0700

```Hi,
I got an error message which I don't understand when I was testing the Cronbach's alpha of the factors' scores after doing factor analysis to a few variables. Does anybody know the reason? The followings are my codes and corresponding output. Thank you very much.
Haiyong

. factor pcs3 mcs3 sfindex3 eurq2 depress_score1_rev, pcf
(obs=999)

Factor analysis/correlation                        Number of obs    =      999
Method: principal-component factors            Retained factors =        2
Rotation: (unrotated)                          Number of params =        9

--------------------------------------------------------------------------
Factor  |   Eigenvalue   Difference        Proportion   Cumulative
-------------+------------------------------------------------------------
Factor1  |      2.53089      1.24056            0.5062       0.5062
Factor2  |      1.29033      0.65076            0.2581       0.7642
Factor3  |      0.63956      0.23163            0.1279       0.8922
Factor4  |      0.40794      0.27665            0.0816       0.9737
Factor5  |      0.13129            .            0.0263       1.0000
--------------------------------------------------------------------------
LR test: independent vs. saturated:  chi2(10) = 2182.86 Prob>chi2 = 0.0000

-------------------------------------------------
Variable |  Factor1   Factor2 |   Uniqueness
-------------+--------------------+--------------
pcs3 |   0.7701   -0.5742 |      0.0773
mcs3 |   0.2941    0.9135 |      0.0790
sfindex3 |   0.8191    0.1093 |      0.3172
eurq2 |   0.8432   -0.1475 |      0.2673
depress_sc~v |   0.6853    0.3040 |      0.4380
-------------------------------------------------

. rotate, varimax

Factor analysis/correlation                        Number of obs    =      999
Method: principal-component factors            Retained factors =        2
Rotation: orthogonal varimax (Kaiser off)      Number of params =        9

--------------------------------------------------------------------------
Factor  |     Variance   Difference        Proportion   Cumulative
-------------+------------------------------------------------------------
Factor1  |      2.35621      0.89121            0.4712       0.4712
Factor2  |      1.46500            .            0.2930       0.7642
--------------------------------------------------------------------------
LR test: independent vs. saturated:  chi2(10) = 2182.86 Prob>chi2 = 0.0000

-------------------------------------------------
Variable |  Factor1   Factor2 |   Uniqueness
-------------+--------------------+--------------
pcs3 |   0.9292   -0.2433 |      0.0773
mcs3 |  -0.0702    0.9571 |      0.0790
sfindex3 |   0.7182    0.4087 |      0.3172
eurq2 |   0.8369    0.1797 |      0.2673
depress_sc~v |   0.5211    0.5389 |      0.4380
-------------------------------------------------

Factor rotation matrix

--------------------------------
| Factor1  Factor2
-------------+------------------
Factor1 |  0.9269   0.3752
Factor2 | -0.3752   0.9269
--------------------------------

. predict factor1 factor2
(regression scoring assumed)

Scoring coefficients (method = regression; based on varimax rotated factors)

----------------------------------
Variable |  Factor1   Factor2
-------------+--------------------
pcs3 |  0.44901  -0.29829
mcs3 | -0.15795   0.69985
sfindex3 |  0.26819   0.19996
eurq2 |  0.35170   0.01904
depress_sc~v |  0.16258   0.32000
----------------------------------

. list factor1 factor2 in 1/5

+-----------------------+
|   factor1     factor2 |
|-----------------------|
1. | -1.126762    1.012057 |
2. |         .           . |
3. |  1.324988   -.3843125 |
4. | -1.244299    1.415611 |
5. |  .6138396    .3841043 |
+-----------------------+

. alpha factor1 factor2, std item detail
r(111);

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```