[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Factor Analysis with ordinal and binary variables |

Date |
Wed, 3 Jun 2009 13:32:25 -0500 |

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, stefan.duke@gmail.com <stefan.duke@gmail.com> 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 <bob.yaffee@nyu.edu> 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 <bob.yaffee@nyu.edu> >> Date: Tuesday, June 2, 2009 3:34 pm >> Subject: Re: st: Factor Analysis with ordinal and binary variables >> To: statalist@hsphsun2.harvard.edu >> >> >>> 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: "stefan.duke@gmail.com" <stefan.duke@gmail.com> >>> Date: Tuesday, June 2, 2009 7:51 am >>> Subject: st: Factor Analysis with ordinal and binary variables >>> To: statalist@hsphsun2.harvard.edu >>> >>> >>> > 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. * * 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/

**References**:**st: Factor Analysis with ordinal and binary variables***From:*"stefan.duke@gmail.com" <stefan.duke@gmail.com>

**Re: st: Factor Analysis with ordinal and binary variables***From:*Robert A Yaffee <bob.yaffee@nyu.edu>

**Re: st: Factor Analysis with ordinal and binary variables***From:*Robert A Yaffee <bob.yaffee@nyu.edu>

**Re: st: Factor Analysis with ordinal and binary variables***From:*"stefan.duke@gmail.com" <stefan.duke@gmail.com>

- Prev by Date:
**Re: st: Negative deff values in survey analysis** - Next by Date:
**st: Re: Event studies significance test** - Previous by thread:
**Re: st: Factor Analysis with ordinal and binary variables** - Next by thread:
**RE: st: Factor Analysis with ordinal and binary variables** - Index(es):

© Copyright 1996–2021 StataCorp LLC | Terms of use | Privacy | Contact us | What's new | Site index |