confirmatory factor analysis - calculate the explained variance

[ablond]

Hi, 

I performed a confirmatory factor analysis with proc calis (see code below).

I also want to report the '% of the explained variance' for this model (as this was also reported in the same way by other papers). 

How can I calculate this explained variance? 

Many thanks! 

ods graphics on;

proc calis data = final plots=pathdiagram outstat  = test ;  

factor 

freq_social_role ==> D1a_s,

freq_social_role ==> D2a_s,

freq_social_role ==> D3a_s,

freq_social_role ==> D5a_s,

freq_social_role ==> D6a_s,

freq_social_role ==> D9a_s,

freq_social_role ==> D11a_s,

freq_social_role ==> D12a_s,

freq_social_role ==> D14a_s,

freq_personal_role ==> D4a_s,

freq_personal_role ==> D7a_s,

freq_personal_role ==> D8a_s,

freq_personal_role ==> D10a_s,

freq_personal_role ==> D13a_s,

freq_personal_role ==> D15a_s,

freq_personal_role ==> D16a_s;

pvar 

freq_social_role = 1., 

freq_personal_role = 1.;

fitindex  noindextype on(only)=[chisq df probchi rmsea  srmr bentlercfi];

run; 

ods graphics off;

[sbxkoenk]

I hereby call upon @jiltao .

Koen

[jiltao]

Short answer: PROC CALIS does not have a keyword or an option for explained variance computations.
Long answer: PROC  CALIS uses an approach that is philosophically different from exploratory factor analysis (PROC FACTOR), and so variance explained by factors is not usually considered a very important concept. In PROC FACTOR, factors are extracted and so you almost always want the variance explained information. In PROC CALIS (or confirmatory factor model), factors are hypothesized and the variance explained by the factors is not critical for selecting the number of factors.

You can compute that information from CALIS:

(1) communalities of variables in FACTOR = R-squares in the Squared Multiple Correlations of CALIS.
(2) For the variance explained by the factors, you can do this: (a) Use ODS output to capture the RotatedLoadings table into a SAS data set; (b) The (unweighted) variance explained by the factors is the sum of squares of the loadings in columns. Note that these steps apply to the orthogonal solutions only. For oblique factors, these steps are not applicable (however, you cannot separate the explained variance by oblique factors anyway).

Hope this helps,

Jill

[ablond]

Thank you for the information. 

I was able to calculate the sum of squares of the factor loadings, but how do I obtain than the percentage of explained variance for the model? 

Best wishes,

Astrid