Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Heteroskedastic Probit Model |

Date |
Thu, 22 Apr 2010 12:43:59 +0000 (GMT) |

--- On Thu, 22/4/10, Mustafa Brahim wrote: > you mentioned that "most of the information is comming > from your assumptions (primarily functional form assumptions)" > and you conclude that I do not have a good theoretical > background. I am not doubting your skills or knowledge concerning theory, I only stated that the information used to estimate this model comes mostly from a very specific theory concerning the functional form of the relationship between the residual variance and some explanatory variables, rather than from the data, and that your question indicated that you did not have that particular theory. This is not a personal attack, this theory probably does not exist for most applications. > So because no one tested the model for heteroskedasticity > does not mean that I should not test mine. You suggested > not to use hetprob,the question then is how am I going > to check whether it exists or not? In the end the purpose of a test (or any statistical modeling) is to extract information from the data, so the first step would be figure out whether such information is even present in the data. My argument was that there is so little information on this issue available in the data, that this test only makes sense in very specific situations where you have very specific theories that can help you identify the model. To be concrete: Heteroskedasticity represents a change in the variance of the residual. The residual is the difference between the observed and expected value in your model. In the probit model the "observed" value isn't observed but latent, i.e. not directly observed. So, this model uses the expected value, which is not directly observed (it is a function of your model), the "observed" value, which is not observed (it is latent), it computes a difference between these unobserved things, and than looks at how the variance of this doubly unobserved thing changes over some variables. To quote John Tukey (1986), "Sunset salvo". The American Statistician 40(1): "The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data." Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * 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/

**References**:**Re: st: Heteroskedastic Probit Model***From:*Mustafa Brahim <datotanseri@gmail.com>

- Prev by Date:
**st: AW: changes in -xi: xtmixed- command from Stata 10 to 11** - Next by Date:
**AW: st: AW: changes in -xi: xtmixed- command from Stata 10 to 11** - Previous by thread:
**Re: st: Heteroskedastic Probit Model** - Next by thread:
**Re: st: Heteroskedastic Probit Model** - Index(es):