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RE: st: RE: FW: Running Polychoric Principal Component Analysis in STATA


From   "Essendi H." <H.Essendi@soton.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: FW: Running Polychoric Principal Component Analysis in STATA
Date   Wed, 29 Aug 2012 14:39:47 +0000

Hi Stas,

I have managed to do it-many thanks.

Hildah

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Stas Kolenikov
Sent: 26 August 2012 23:15
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: RE: FW: Running Polychoric Principal Component Analysis in STATA

Hildah,

-poychoricpca- has option -score-, as the help file explains. It produces the principal components.

On Fri, Aug 24, 2012 at 2:58 PM, Essendi H. <H.Essendi@soton.ac.uk> wrote:
> Hi,
>
> I have run my Polychoric PCA with 30 variables and these are my results. How do I extract the principal components?
>
>
>
> k    Eigenvalues        Proportion      explained       Cum. explained
>
> 1     9.875133  0.329171                0.329171
> 2     3.914605  0.130487                0.459658
> 3     2.199687  0.073323                0.532981
> 4     1.972968  0.065766                0.598746
> 5     1.806116  0.060204                0.658950
> 6     1.491586  0.049720                0.708670
> 7     1.057610  0.035254                0.743924
> 8     0.957563  0.031919                0.775842
> 9     0.876737  0.029225                0.805067
> 10     0.808630 0.026954                0.832021
> 11     0.721940 0.024065                0.856086
> 12     0.617829 0.020594                0.876680
> 13     0.568042 0.018935                0.895615
> 14     0.534358 0.017812                0.913427
> 15     0.474645 0.015821                0.929248
> 16     0.432420 0.014414                0.943662
> 17     0.394679 0.013156                0.956818
> 18     0.350109 0.011670                0.968489
> 19     0.317694 0.010590                0.979078
> 20     0.272341 0.009078                0.988156
> 21     0.266147 0.008872                0.997028
> 22     0.228569 0.007619                1.004647
> 23     0.182232 0.006074                1.010721
> 24     0.134601 0.004487                1.015208
> 25     0.073532 0.002451                1.017659
> 26     0.002814 0.000094                1.017753
> 27     0.000000 0.000000                1.017753
> 28    -0.000000 -0.000000               1.017753
> 29    -0.009973 -0.000332               1.017420
> 30    -0.522612 -0.017420               1.000000
>
>
>
> scalars:
>         r(lambda30)     =       -.5226117872285307
>         r(lambda29)     =       -.0099733429209876
>         r(lambda28)     =       -2.91788802401e-11
>         r(lambda27)     =       2.91791708536e-11
>         r(lambda26)     =       .0028136759119166
>         r(lambda25)     =       .0735315467859793
>         r(lambda24)     =       .1346013978294836
>         r(lambda23)     =       .1822315003459927
>         r(lambda22)     =       .228568953051127
>         r(lambda21)     =       .2661472213481918
>         r(lambda20)     =       .2723408357592857
>         r(lambda19)     =       .3176943611403527
>         r(lambda18)     =       .3501089523760873
>         r(lambda17)     =       .3946787848401978
>         r(lambda16)     =       .432420025218819
>         r(lambda15)     =       .4746446780762609
>         r(lambda14)     =       .5343577888749866
>         r(lambda13)     =       .5680416974993906
>         r(lambda12)     =       .6178288336363039
>         r(lambda11)     =       .7219402529310105
>         r(lambda10)     =       .8086298902211778
>         r(lambda9)      =       .8767365013048373
>         r(lambda8)      =       .9575625979499038
>         r(lambda7)      =       1.05760970715606
>         r(lambda6)      =       1.491586326478875
>         r(lambda5)      =       1.806116092435452
>         r(lambda4)      =       1.972968399660107
>         r(lambda3)      =       2.19968656497797
>         r(lambda2)      =       3.914605324771372
>         r(lambda1)      =       9.87513321956839
>
> Thanks,
> HIldah
>
>
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Essendi H.
> Sent: 22 August 2012 15:00
> To: statalist@hsphsun2.harvard.edu
> Subject: st: FW: Running Polychoric Principal Component Analysis in 
> STATA
>
> Dear STATA,
>
> How can I run Polychoric principal component analysis in STATA? . I have likert scale data on wellbeing and I would like to prepare wealth quintiles based on these subjective responses. The challenge I am facing however is how to prepar e my variables before running this. I am not sure whether I need to recode them into dummy variables or just rung these with all the ordered category?.  Also kindly advice on how to do this step by step.
>
> Many thanks,
> Hildah
>
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--
-- Stas Kolenikov  ::  http://stas.kolenikov.name
-- Senior Survey Statistician, Abt SRBI  ::  work email kolenikovs at srbi dot com
-- Opinions stated in this email are mine only, and do not reflect the position of my employer

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