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| From | "Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | R: st: Tobit regression Model |
| Date | Sun, 2 Dec 2012 16:57:11 +0100 |
As Adel has probably heard during some statistics class, according to a long lasting rule-of-thumb, researcher should have around 20 observations for each predictor included in her/his multiple linear regression model. I would assume that this guidance may sound interesting for Tobit models, too. Last time I came across this recommendation was in: Katz MH. Multivariable Analysis. A Practical Guide for Clinicians, 2nd edition. Cambridge: Cambridge University Press, 2006: 81. Kindest Regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Adel Enpaya Inviato: domenica 2 dicembre 2012 11:25 A: 'statalist@hsphsun2.harvard.edu' Oggetto: RE: st: Tobit regression Model Dear Stateliest I have data set of 183 observations and 36 variables include 13 dummy variables when I run Tobit regression model, No results obtain, but if if I reduce the number of variable , I can obtains result, is there any relationship between number of variables, number and observations and (degree of freedom) Thanks Adel * 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/