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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: measures of fit using svy:regress |

Date |
Sat, 22 Dec 2007 17:02:31 -0500 |

You can estimate adjusted r-square directly as Adj R2 = 1- (residual SD^2)/var(Y)

Estimate of var(Y). See:

http://www.stata.com/support/faqs/stat/supweight.html

for an estimate of the SD of Y.

For an estimate of the Residual SD

Here's a method I previously posted to compute the Residual SD and a CI for it. If you incorporated the formula for the population variance into nlcom, you could get a CI for the ratio of (residual Var)/Var(Y) and thus a CI of your adjusted R2.

/***********************************CODE STARTS**********************************************************/

/* First, a program to compute a 95% CI after -nlcom- has estimated a parameter on the log scale*/

capture program drop _all

program antilog

local lparm el(r(b),1,1)

local se sqrt(el(r(V),1,1))

local bound invttail(e(df_r),.025)*`se'

local parm exp(`lparm')

local ll exp(`lparm' - `bound')

local ul exp( `lparm' + `bound')

di "parm =" `parm' " llim = " `ll' " ul = " `ul'

end

webuse nhanes2, clear

svyset

svy : reg weight height

predict predicted

gen resid= weight-predicted

gen resid2=resid*resid

svy: mean resid2

nlcom .5*log(_b[resid2]) //residual SD

nlcom log(_b[resid2]) //residual variance

antilog

/***************************CODE ENDS****************************************************/

On Dec 21, 2007, at 10:08 PM, jbowdoin@schoolph.umass.edu wrote:

I am using svy: regress. Are there other measures of fit available besides R-

squared? Can I obtain the adjusted R-squared or root MSE?

*

* 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/

**References**:**st: measures of fit using svy:regress***From:*jbowdoin@schoolph.umass.edu

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