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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Exploratory factor analysis using a mix of categorical and continuous variables |

Date |
Fri, 3 Feb 2012 09:52:33 +0000 |

I don't see that this can be easily classified as correct or incorrect. Some people recommend strongly against such a mix, and some people would argue that the pragmatic defence is whether it provides interesting or useful results. As you yourself have labelled the exercise "exploratory" the acid test is surely what do you learn from the data by examining the results. This is a cross-disciplinary list and we can only report our own perspectives. In what is nominally my own discipline, geography, factor analysis in the sense of an exploratory exercise throwing all the data into one pot, stirring and seeing what you got, was probably the most popular technique of all in the late 1960s and early 1970s. I met several people whose one statistical idea was to read everything into SPSS and do a factor analysis. I even met some people who did not know that there were simpler statistical techniques. In geography this fashion faded rapidly as too many people did not understand what they were doing or found no useful new results. However, I am now touching on quite different stories. In terms of your question, my only guess is that from your variable names you have a ragbag here and you won't find much interesting or useful structure. It is better to decide what are your response or outcome variables that you most want to explain or predict and think how those might be modelled. The basic problem is not soluble by using a slightly different multivariate command. Having a mix of predictor types, dummies, categorical and continuous variables, is of course a soluble problem. Nick On Fri, Feb 3, 2012 at 9:32 AM, Urmi Bhattacharya <ub3@indiana.edu> wrote: > I am using exploratory factor analysis to generate factor loadings and > the corresponding uniqueness values using 16 variables. I have a mix > of dummy variables (taking values 1 or 0), categorical variables > (positive integers), and continuous variables. I am using the > following command: > > factor govt_school chais_desk_s schl_toilet_s schl_water_s > hrs_electric_s num_classoutdoor_s num_mixedgrade_s reg_fee_gen_s > tuit_fee_ gen_s pupil_teach_s inservice_training_s library_s > computer_use_s playgrnd_s formal_teach_eval_s distance_primaryschool, > ipf factor(1). > > My question is whether this is the correct procedure to use when I > have variables that are not continuous? If not, is there a command in > Stata that better handles this? * * 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/

**Follow-Ups**:**Re: st: Exploratory factor analysis using a mix of categorical and continuous variables***From:*Urmi Bhattacharya <ub3@indiana.edu>

**References**:**st: Exploratory factor analysis using a mix of categorical and continuous variables***From:*Urmi Bhattacharya <ub3@indiana.edu>

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