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From |
Steven Samuels <sjhsamuels@earthlink.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: model building survey data. WAS st: adjusted R2 in survey regression |

Date |
Thu, 16 Oct 2008 10:30:11 -0400 |

Aca:

**************************CODE BEGINS************************** sysuse auto,clear gen psu= mod(_n, 10) // artificial cluster svyset psu [pweight=rep78] reg mpg weight predict yhat gen yhat2= yhat*yhat svy: reg mpg yhat yhat2 //significance of yhat2 is the link test ***************************CODE ENDS***************************

**************************CODE BEGINS************************** svy: reg mpg weight trunk length test trunk length //tests for significance of adding trunk and length ***************************CODE ENDS***************************

**************************CODE BEGINS************************** fracpoly reg mpg weight [pweight=weight], vce(cluster psu) ***************************CODE ENDS***************************

On Oct 15, 2008, at 8:51 PM, Aca N.T. wrote:

Steve had shown how -dlist- can sort my problem out anyway. In this case, however, I was wondering if -linktest- can be used as a subtitute for adjusted R2 (or should be more as complementary test?). I mean, does -linktest- act like -lrtest- which is to compare LR from one model to another when running a simple logistic regression so we can see how a model is improved? Aca.On Thu, Oct 16, 2008 at 5:01 AM, Stas Kolenikov<skolenik@gmail.com> wrote:On Wed, Oct 15, 2008 at 2:23 AM, Aca N.T. <acant29@gmail.com> wrote:I'm puzzled with model building using -svy: reg- for there is no adjusted R squared produced. Is there an alternative test for this?Uhm... alternative test for what? If Stata does not produce something really obvious, like R2 or adjusted R2, then it means they looked into this and decided it had dubious statistical properties. R2 is an iid data concept: each residual is a random variable that has a certain variance, and that variance is the same for all observations. The complex survey setting does not really have that concept: the explanatory and response variables are in fact fixed, and the randomness comes from samplingprocedure only. The regression formulas may look the same (in theend,there are just this many ways to minimize a sum of squares...) but interpretation of a few things is different. So one can probably talk about population variance of residuals, as a relatively meaningful quantity, but there is no analogue of the concept of the variance of each individual residual -- that's a fixed quantity. If there is no population analogue of R2, it should not be reported to the user, and that makes perfect sense. -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * 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/

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**Follow-Ups**:**Re: model building survey data. WAS st: adjusted R2 in survey regression***From:*"Aca N.T." <acant29@gmail.com>

**References**:**st: adjusted R2 in survey regression***From:*"Aca N.T." <acant29@gmail.com>

**Re: st: adjusted R2 in survey regression***From:*"Stas Kolenikov" <skolenik@gmail.com>

**Re: st: adjusted R2 in survey regression***From:*"Aca N.T." <acant29@gmail.com>

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