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From | Austin Nichols <austinnichols@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: goodness of fit measure fir ivtobit |
Date | Tue, 25 Sep 2012 09:32:13 -0400 |
Anat (Manes) Tchetchik <anatmanes@gmail.com>: 1. You can specify that max as exposure, but it sounds a bit odd to me--why not just include ln(number_of_years_rel_abroad) and ln(age-17) as predictors and let the regression estimate the coefs? If one coef turns out to be close to one, then it looks like an exposure variable: an exposure X just means that ln(X) enters with a coef of one (elasticity of one). An offset X just means that X enters with a coef of one (semi-elasticity of one). 3. Yes, predict yhat and calculate squared corr of y and yhat as a pseudo-R-squared. On Tue, Sep 25, 2012 at 7:49 AM, Anat (Manes) Tchetchik <anatmanes@gmail.com> wrote: > Austin hi, > I have read the material regarding the ivpois model you have referred > me to and ran it on my data set. The results look pretty plausible . > Just before sticking to this model I have few last questions: > > 1. Can I use the exposure variable (in my case the maximum of the two > values: respondent's adulthood years and and the no. of years his/her > relative is staying abroad) also as an independent var.? (or given > that I do it- I should not use the exposure option) > > 2. I'm not sure i understand when I should use the exposure option and > when the offset one > > 3. Do I calculate goodness of fit measure using the same procedure you > recommended earlier > (http://www.stata.com/support/faqs/statistics/r-squared/) ? > > Thank you very much! > Anat > > On Mon, Sep 24, 2012 at 6:38 PM, Austin Nichols <austinnichols@gmail.com> wrote: >> >> Anat (Manes) Tchetchik <anatmanes@gmail.com> : >> Indeed, no censoring in your model. You have exactly the case I >> referred to when I wrote "I suspect you have a lower limit at zero >> which is actually a very low conditional mean rounded down to zero." >> Unless you believe that the Tobit model somehow correctly captures >> bunching at zero due to utility functions which would imply a negative >> demand for travel abroad, if such a thing were possible, which is >> implausible at best, you are much better off assuming that people with >> zero travel abroad simply have very low demand, and a group that has a >> conditional mean of 1/100000 trips will indeed have a lot of zeros >> observed. The -ivpois- package on SSC, and the -gmm- specifications >> that supersede it, are designed to allow instrumental variables in a >> count model, or a regression with nonnegative outcomes more generally: >> http://www.stata.com/meeting/boston10/boston10_nichols.pdf >> http://fmwww.bc.edu/repec/bocode/i/ivpois.html >> >> On Mon, Sep 24, 2012 at 10:54 AM, Anat (Manes) Tchetchik >> <anatmanes@gmail.com> wrote: >> > I haven't thought about the count model, I will definitely try to run >> > it! thanks much! >> > >> > On Mon, Sep 24, 2012 at 5:38 PM, Maarten Buis <maartenlbuis@gmail.com> wrote: >> >> That does not sound like censoring at all. I would think of this as a >> >> regular count model. There are examples on how to deal with such an >> >> iv-model in -help gmm-. >> >> >> >> Hope this helps, >> >> Maarten >> >> >> >> On Mon, Sep 24, 2012 at 4:11 PM, Anat (Manes) Tchetchik >> >> <anatmanes@gmail.com> wrote: >> >>> Austin Hi, >> >>> Thank you very much for your reply! >> >>> What I have as a dependent var. are 500 respondents' reports of the >> >>> number of times they travelled abroad to visit their friends and >> >>> relatives over the course of their adult lives. Some respondents yet, >> >>> who have relatives abroad, did not travel at all. >> >>> So the observations are censored at zero, with mean =2.2, max =50 and >> >>> stdev= 3.8. >> >>> Do you think in that case that the general methods of moments will be better? >> >>> Thanks much!!! >> >>> Anat >> >>> >> >>> On Sun, Sep 23, 2012 at 5:49 AM, Austin Nichols <austinnichols@gmail.com> wrote: >> >>>> >> >>>> Anat (Manes) Tchetchik <anatmanes@gmail.com>: >> >>>> You can always -predict- and compute the squared correlation of >> >>>> predictions with observed values: >> >>>> http://www.stata.com/support/faqs/statistics/r-squared/ >> >>>> but are you sure your -ivtobit- model is justified? What is the >> >>>> process that results in observations being censored? I suspect you >> >>>> have a lower limit at zero which is actually a very low conditional >> >>>> mean rounded down to zero--am I right? You may be better off with a >> >>>> -gmm- model. >> >>>> >> >>>> On Sat, Sep 22, 2012 at 5:33 PM, Anat (Manes) Tchetchik >> >>>> <anatmanes@gmail.com> wrote: >> >>>> > Dear statalisters, >> >>>> > >> >>>> > I wonder if anyone knows any goodness of fit that is appropriate for >> >>>> > tobit with endogenous >> >>>> > variables (ivtobit). Not as in "regular" tobit, stata does not report any >> >>>> > goodness of fit measure, any idea how to estimate such a measure? >> >>>> > Any response will be greatly appreciated.. * * 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/