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From |
Garry Anderson <[email protected]> |

To |
[email protected] |

Subject |
RE: st: right censoring of dependent and independent variable |

Date |
Thu, 29 May 2008 23:32:50 +1000 |

Thank you Maarten for the excellent graphics example. Including and excluding these right censored x values in a tobit analysis makes very little difference to the slope. Cheers, Garry ________________________________ From: [email protected] on behalf of Maarten buis Sent: Thu 29/05/08 22:43 To: [email protected] Subject: Re: st: right censoring of dependent and independent variable --- Garry Anderson <[email protected]> wrote: > I have data where both the dependent and independent variable are > right censored and continuous. Although intreg, cnreg or tobit can > handle censoring of the dependent variable, they do not seem to allow > censoring of the independent variable. Both the instruments can only > measure to a maximum value, 30% of values are right censored on the Y > variable and 15% on the X variable. > > I would welcome suggestions as to how to incorporate right censoring > of the independent variable? In the graph below you can see that selection on the x variable is much less of a problem than selection on the y variable. A part of the data is turned into influential outliers, by selecting on the y. In the example it is the upper right part of the observed values that pull the regression line down. However, the same does not happen when you select on x. With regression you model the mean of y conditional on x, the fact that you don't observe all values of x, is unfortunate (loss of power) but not disastrous. Things become obviously more complicated when you are interested in any non-linearities in the effect of x. Hope this helps, Maarten *----------------------- begin example ------------------------ clear set seed 12345 matrix C = (1, .5 \ .5, 1) drawnorm x y, n(1000) corr(C) twoway scatter y x if x < 1, aspect(1) xline(1) || /// scatter y x if x >= 1, msymbol(oh) mcolor(gs10) || /// lfit y x , lpattern(solid) lcolor(green) || /// lfit y x if x < 1, lpattern(solid) lcolor(red) /// title(selection on x) name(x, replace) /// legend(order( 1 "observed" /// 2 "censored" /// 3 "true" /// 4 "estimated") /// rows(2)) twoway scatter y x if y < 1, aspect(1) yline(1) || /// scatter y x if y >= 1, msymbol(oh) mcolor(gs10) || /// lfit y x , lpattern(solid) lcolor(green) || /// lfit y x if y < 1, lpattern(solid) lcolor(red) /// title(selection on y) name(y, replace) /// legend(order( 1 "observed" /// 2 "censored" /// 3 "true" /// 4 "estimated") /// rows(2) colfirst) grc1leg y x *------------------------ end example --------------------------- (For more on how to use examples I sent to the Statalist, see http://home.fsw.vu.nl/m.buis/stata/exampleFAQ.html ) For this example to run you need to download the -grc1leg- package, see: -findit grc1leg-. ----------------------------------------- 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 Email http://uk.docs.yahoo.com/nowyoucan.html * * 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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**References**:**Re: st: right censoring of dependent and independent variable***From:*Maarten buis <[email protected]>

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