I wrote -polychoric- package some while ago... never perfectly
polished it though, and it breaks down when overloaded with large
amounts of poor data. Joreskog's ideas can be found on LISREL website
-- google Joreskog+ordinal.
On Wed, Jun 3, 2009 at 5:12 AM, [email protected]
<[email protected]> wrote:
> Hi ya'll,
> thanks for you advice, so I know now where to look.
> Currently, I don't have a particular problem. I was just curious where
> to look and how to proceed when encountering such a mix of variables.
> Best,
> Stefan
>
>
> On Tue, Jun 2, 2009 at 10:04 PM, Robert A Yaffee <[email protected]> wrote:
>> On this issue, the polyserial and polychoric correlations
>> can be used for binary and ordinal variables, respectively,
>> as input to a factor analysis, according to Joreskog and
>> Sorbom, who did the research back in the 1980s.
>> Bengt Muthen has also studied this matter.
>> Both teams have incorporated their findings into their
>> structural equation modeling packages.
>> - Bob
>>
>>
>> Robert A. Yaffee, Ph.D.
>> Research Professor
>> Silver School of Social Work
>> New York University
>>
>> NSF grant:
>> http://www.colorado.edu/ibs/es/nuclear_disaster_risk/principal_investigators.html
>> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf
>>
>> CV: http://homepages.nyu.edu/~ray1/vita.pdf
>>
>> ----- Original Message -----
>> From: Robert A Yaffee <[email protected]>
>> Date: Tuesday, June 2, 2009 3:34 pm
>> Subject: Re: st: Factor Analysis with ordinal and binary variables
>> To: [email protected]
>>
>>
>>> Stefan,
>>> Karl Joreskog and Dag Sorbom
>>> analyzed the problem back in the 1980s and found
>>> that you could use polyserial and polychoric correlations
>>> for a factor analysis of dichotomous or ordinal variables.
>>> If the ordinal variables have at least 15 levels they can
>>> be treated as continuous.
>>> They have incorporated this finding in their program for
>>> structural equation modeling.
>>> Regards,
>>> Bob Yaffee
>>>
>>> Bengt Muthen may have also written
>>> on this subject in the 1980s or early 1990s.
>>>
>>>
>>> Robert A. Yaffee, Ph.D.
>>> Research Professor
>>> Silver School of Social Work
>>> New York University
>>>
>>> NSF grant:
>>> http://www.colorado.edu/ibs/es/nuclear_disaster_risk/principal_investigators.html
>>> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf
>>>
>>> CV: http://homepages.nyu.edu/~ray1/vita.pdf
>>>
>>> ----- Original Message -----
>>> From: "[email protected]" <[email protected]>
>>> Date: Tuesday, June 2, 2009 7:51 am
>>> Subject: st: Factor Analysis with ordinal and binary variables
>>> To: [email protected]
>>>
>>>
>>> > Hello,
>>> >
>>> > I have question concerning factor analysis on variables with different
>>> > measurement levels.
>>> >
>>> > The questionnaire consists of binary and ordinal variables. If I would
>>> > have just binary variables, I would use the tetrachoric correlation
>>> > coefficients. For the ordinal I assume approx. normality and then use
>>> > the ordinary factor analysis capability.
>>> >
>>> > But what do I do when I have both variables? Is it an option to
>>> > construct the variance-covariance matrix by hand? And what do I take
>>> > for the correlation between binary and ordinal?
>>> >
>>> > Maybe is there a model class which takes care of that, that yields
>>> > similar outcomes as factor analysis but can deal with such kind of
>>> > data (e.g. correspondence analysis).
>>> >
>>> > I am grateful for every hint.
>>> >
>>> > Best,
>>> > Stefan
>>> > *
>>> > * For searches and help try:
>>> > * http://www.stata.com/help.cgi?search
>>> > * http://www.stata.com/support/statalist/faq
>>> > * http://www.ats.ucla.edu/stat/stata/
>>> *
>>> * For searches and help try:
>>> * http://www.stata.com/help.cgi?search
>>> * http://www.stata.com/support/statalist/faq
>>> * http://www.ats.ucla.edu/stat/stata/
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
*
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