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From |
Maarten buis <[email protected]> |

To |
[email protected] |

Subject |
Re: SV: SV: st: From probit to dprobit to interpretation |

Date |
Fri, 11 Jan 2008 16:22:40 +0000 (GMT) |

I that case you would get the expected number of successes if everybody had value 1 for X and the expected number of successes if everybody had 0 for X. -- Maarten --- [email protected] wrote: > Does not that mean that this, > > > Turning of the effect of X: > > 0.99%*1000000=9900 > > > > Turning on the effect of X: > > 0.29%*1000000=2900 > > > > Then, the way I have understood this: > > Discrete change, reduction induced by x=9900-2900=7000? > > Will be wrong? Here I have applied the on and off effects on the > total sample. > In the model n=1000000, and there is 500000 members of the program > (x=1), thus 600000 are not member. > I the example above I argue that x causes a reduction in the 1000000 > sample of 7000, due to the dicrete change of .7%. > > Alex > > -----Opprinnelig melding----- > Fra: [email protected] > [mailto:[email protected]] P� vegne av Maarten > buis > Sendt: 11. januar 2008 16:11 > Til: [email protected] > Emne: Re: SV: st: From probit to dprobit to interpretation > > The separate probabilities need to be applied to their group, but the > discrete change needs to be applied to the total sample. > > --- [email protected] wrote: > > > Thanks Maarten! That is very helpful. I guess what have been > confusing > > for me then is how to apply the predicted -0.7% discrete change > (the > > difference between turning on and off the effect), on the full > sample > > as I have done below, or only on those 500000 that are signed up to > > > the membership program. The difference offcourse making a huge > impact > > on the result. > > > > Best wishes, > > Alexander > > > > -----Opprinnelig melding----- > > Fra: [email protected] > > [mailto:[email protected]] P� vegne av Maarten > buis > > Sendt: 11. januar 2008 14:16 > > Til: stata list > > Emne: RE: st: From probit to dprobit to interpretation > > > > What you say is correct and there is no contradiction between all > > these statements. From a probit model you can derive predicted > > proportions, and with predicted proportions you can derive > predicted > > counts in your sample (and if you know the size of your population > the > > predicted counts in your population). > > > > Hope this helps, > > Maarten > > > > --- [email protected] wrote: > > I have estimated a probit model where n=1000 000 customers with > only > > 1 independent dummy variable (x) (for the sake of clarity), and get > > > the following estimated coefficients: > > > > y_pred=-2.33-0.431*x (x being significant) > > > > No the way I understand this is that these coefficients, except for > > > the signs and significance level, is hard to interpret. Thus, I can > > > derive it as a probability model, and then again calculate > > probabilities from any table with standard cumulative normal > > distribution values. Turning on and off x will give me the discrete > > > change, thus > > > > Turning off the effect of X thus gives me: > > y_pred=-2.33-(0.431*0) and > > Pr(z<2.33)=0.99% > > > > Tuning on the effect > > y_pred=-2.33-(0.431*1)=-2.761 and > > Pr(z<2.761)=0.29% > > > > The difference between these probabilities is the discrete change, > and > > this change can be directly estimated using a dprobit model in > Stata? > > Discrete change=0.99-0.29=-0.7% > > > > Most textbooks stops here, and I think that so far I am on the > right > > track - but I want to interpret this probability in terms of what > this > > x induced effect means in terms of my sample... > > > > In this particular model my sample is 1000000, and x=1 is a > membership > > program of which there are 500000 members. Would it be correct to > > assume that the discrete change estimated above in terms of > customers > > could be interpreted as following: > > > > Turning of the effect of X: > > 0.99%*1000000=9900 > > > > Turning on the effect of X: > > 0.29%*1000000=2900 > > > > Then, the way I have understood this: > > Discrete change, reduction induced by x=9900-2900=7000? > > > > > > > > ----------------------------------------- > > Maarten L. Buis > > Department of Social Research Methodology Vrije Universiteit > Amsterdam > > Boelelaan 1081 > > 1081 HV Amsterdam > > The Netherlands > > > > visiting address: > > Buitenveldertselaan 3 (Metropolitan), room Z434 > > > > +31 20 5986715 > > > > http://home.fsw.vu.nl/m.buis/ > > ----------------------------------------- > > > > > > ___________________________________________________________ > > Support the World Aids Awareness campaign this month with Yahoo! > For > > Good http://uk.promotions.yahoo.com/forgood/ > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > > ----------------------------------------- > Maarten L. Buis > Department of Social Research Methodology Vrije Universiteit > Amsterdam Boelelaan 1081 > 1081 HV Amsterdam > The Netherlands > > visiting address: > Buitenveldertselaan 3 (Metropolitan), room Z434 > > +31 20 5986715 > > http://home.fsw.vu.nl/m.buis/ > ----------------------------------------- > > > __________________________________________________________ > Sent from Yahoo! Mail - a smarter inbox http://uk.mail.yahoo.com > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- __________________________________________________________ Sent from Yahoo! Mail - a smarter inbox http://uk.mail.yahoo.com * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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