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From |
Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
SV: st: exploratory factor analysis with dichotomous and continuous data |

Date |
Thu, 22 Nov 2012 20:27:07 +0000 |

The idea is to do an exploratory data-analysis (followed by a CFA) on 11 clinical variables, some dichotomous and some continuous, to reduce the amount of variables in the score. The only variable having this "structural zero problem" is the one described here. Do I really have to change the plan, or is there another way? Do have to write the article for my PhD and appreciate every help I can get here, since I am quite new to the subject (as you probably already guessed...) Frauke -----Oprindelig meddelelse----- Fra: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] På vegne af Nick Cox Sendt: 22. november 2012 08:25 Til: statalist@hsphsun2.harvard.edu Emne: Re: st: exploratory factor analysis with dichotomous and continuous data I guess the only other answers are that this variable is unsuitable for your method or that the method is unsuitable for your data. Nick On Thu, Nov 22, 2012 at 6:31 AM, Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk> wrote: > Thank you for your answer, Jay. > I guess, judging from your description, that it is a structural zero. Hemoptysis means coughing up blood, which isn´t really possible without coughing. > However those are not the only variables, so is there a way to loop this problem in the analysis? > I don´t think it makes sense to add pseudo-cases. JVerkuilen (Gmail) > On Wed, Nov 21, 2012 at 5:37 AM, Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk> wrote: >> >> I found some useful threads on the net, so now I know why I get the message; It is due to one of the dichotomous variables having 0 observations in one of the 2x2 tables: >> haemoptysi | cough >> s | 1 2 | Total >> -----------+----------------------+---------- >> 1 | 168 0 | 168 >> 2 | 896 53 | 949 >> -----------+----------------------+---------- >> Total | 1,064 53 | 1,117 >> >> What I could not find, was a solution on, how to deal with this in order to be able to run an EFA. >> I hope you can help me with this. > > First of all is this a sampling zero or a structural zero, i.e., > something that is impossible (silly example: male patients of an > OB/GYN)? I simply don't know the substance to be able to judge. If > it's a structural zero you need to decide if the EFA model is even > appropriate. I ask because this is a pretty big sample and thus a > sampling zero seems unlikely, but I really don't know. > > If not, you can add a certain number of pseudo-cases to all cells in > your contingency table. In the loglinear model literature this is > called "flattening" and is often necessary to get reasonable > estimates. > > Essentially you have to do this in small doses, adding one, then two > then three, cases, to make sure that the resulting correlations don't > shift dramatically. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: exploratory factor analysis with dichotomous and continuous data***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**References**:**st: exploratory factor analysis with dichotomous and continuous data***From:*Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk>

**Re: st: exploratory factor analysis with dichotomous and continuous data***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**SV: st: exploratory factor analysis with dichotomous and continuous data***From:*Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk>

**Re: st: exploratory factor analysis with dichotomous and continuous data***From:*Nick Cox <njcoxstata@gmail.com>

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