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From |
Ángel Rodríguez Laso <angelrlaso@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: RE: Residuals in svy:intreg |

Date |
Fri, 1 Jun 2012 15:22:30 +0200 |

Well, at least the analysis of residuals has made me aware that the outcome needed a transformation, because top censored data were clear outliers. That has improved the model. Many thanks again. Angel Rodriguez-Laso 2012/6/1 Nick Cox <njcoxstata@gmail.com>: > I can't add much to my previous answer. Clearly you have in mind that > censoring complicates things. But what does "OK" mean here? That it is > technically correct? That you cannot be misled? That someone in > authority might object or assert that you are wrong? I think it > depends what you are doing, in what circumstances, and who is judging > on what criteria. > > For example, I think it can be helpful to look at residual plots. > Frequently they don't help, but when they do, it is in an important > way. > > Some economists (in particular) seem to object to anything that is not > a formal test as arbitrary, subjective and lacking in rigour. So, they > don't seem to do things like that. > > But I can see that any formal procedure that treats residuals from an > interval regression and ignores their origin is likely to be suspect. > > Nick > > On Fri, Jun 1, 2012 at 9:43 AM, Ángel Rodríguez Laso > <angelrlaso@gmail.com> wrote: >> Then, would it be OK for individuals with censored variables to >> consider that their observed values are those where censoring took >> place? Shouldn't there be some 'allowance' for error in the observed >> values, as I suppose there is when calculating the interval >> regression? >> >> Thank you very much. >> >> Angel Rodriguez-Laso >> >> 2012/6/1 Nick Cox <njcoxstata@gmail.com>: >>> I think there are two levels to this. >>> >>> For informal (e.g. graphical) analysis, nothing is fundamentally >>> different, so that absence of pattern is good news and presence of >>> pattern may make you think about whether the model can be improved. >>> >>> For formal analysis, I don't know of any published procedures either, >>> but if you invented your own, simulation may be the most practical way >>> to establish their properties. >>> >>> On Fri, Jun 1, 2012 at 8:49 AM, Ángel Rodríguez Laso >>> <angelrlaso@gmail.com> wrote: >>>> Dear Nick, >>>> >>>> Thank you for your answer. >>>> >>>> Unfortunately, after intensive search in the web I haven´t been able >>>> to find any document on the use of residuals in interval regression or >>>> the checking of assumptions of interval regression in the survey >>>> setting. Of the two references that Stata manual v11 gives for an >>>> introduction to interval regression (Wooldridge, J. M. 2009. >>>> Introductory Econometrics: A Modern Approach. 4th ed. Cincinnati, OH: >>>> South-Western. Davidson, R., and J. G. MacKinnon. 2004. Econometric >>>> Theory and Methods. New York: Oxford University Press.), I've only had >>>> access to Wooldridge's and it does not say anything on how to use >>>> residuals in this context. >>>> >>>> I suppose the difficult part in calculating (observed-predicted >>>> values) is assigning values from which censoring takes place as >>>> observed values for individuals with censored data. >>>> >>>> Angel Rodriguez-Laso >>>> >>>> 2012/5/31 Nick Cox <n.j.cox@durham.ac.uk>: >>>>> I doubt that this was the question, but I am assuming here that if you want residuals, then it's just an extra line calculating the residuals as difference between observed and predicted. >>>>> >>>>> Nick >>>>> n.j.cox@durham.ac.uk >>>>> >>>>> >>>>> -----Original Message----- >>>>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox >>>>> Sent: 31 May 2012 11:09 >>>>> To: 'statalist@hsphsun2.harvard.edu' >>>>> Subject: st: RE: Residuals in svy:intreg >>>>> >>>>> Still true in 12.1. >>>>> >>>>> I would guess rather that as residuals need some careful interpretation with -intreg-, StataCorp lets users make their own decisions about working with them. >>>>> >>>>> If you can refer us to literature defining and using residuals carefully for -intreg-, that would strengthen the case for adding them to official Stata. >>>>> >>>>> Nick >>>>> n.j.cox@durham.ac.uk >>>>> >>>>> Ángel Rodríguez Laso >>>>> >>>>> I'm working with Stata 9.2 for Windows. >>>>> >>>>> I have to carry out an interval regression with survey data, because >>>>> there are top and bottom censored values. I've noticed Stata version >>>>> 9.2 does not provide residuals for this model. It calculates predicted >>>>> values, but if it does not provide (observed-predicted values), there >>>>> must be a good reason. >>>>> >>>>> I understand that, because I'm in a survey environment, I do not have >>>>> to check for homoskedasticity of residuals and that they are not >>>>> expected to be independent. But residuals would still be useful to >>>>> check for model lack of fit (nonlinearity and presence for influential >>>>> points and outliers). Do you know of any alternatives? >>> >>> * >>> * 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/ >> >> * >> * 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/ > > * > * 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/ * * 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: RE: RE: Residuals in svy:intreg***From:*Ángel Rodríguez Laso <angelrlaso@gmail.com>

**Re: st: RE: RE: Residuals in svy:intreg***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: RE: RE: Residuals in svy:intreg***From:*Ángel Rodríguez Laso <angelrlaso@gmail.com>

**Re: st: RE: RE: Residuals in svy:intreg***From:*Nick Cox <njcoxstata@gmail.com>

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