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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
AW: st: AW: Simulating stepwise regression |

Date |
Fri, 7 Aug 2009 15:09:35 +0200 |

<> I am sensing that this is more about the # of covariates retained by -sw- than the names - which are made up and meaningless anyway. So here is code that allows you to vary the sample size (option -obs-) and the # of regressors to feed to -sw-, with appropriate defaults. It returns R Squared adjusted and the number of retained regressors... ************* capt prog drop sim version 10.1 program define sim, rclass vers 10.1 syntax [, obs(integer 100) NUMber(integer 5)] drop _all set obs `obs' gen y = invnorm(uniform()) forv i=1/`number'{ gen x`i' = rnormal() } stepwise, pr(.2): regress y x* ret sca r2a= e(r2_a) qui indeplist ret sca numofregre=/* */ `:word count `r(X)'' end //run it once just to see sim, obs(50) num(3) ret li //simulate it! simulate rsqadj=r(r2a)/* */ numofreg=r(numofregre), /* */ reps(100): sim, obs(100) list, noo h(30) ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von John Antonakis Gesendet: Freitag, 7. August 2009 12:18 An: statalist@hsphsun2.harvard.edu Betreff: Re: st: AW: Simulating stepwise regression That's very helpful; thanks Martin. To extend the below, how would I simulate the r-square? That is, I want to run the simulation say 100 times, and then obtain the mean r-square from each simulation. Thus, I can show, at a specific sample size (n=100) and number of independent variables (k=5), what the r-square would be just by chance alone. As an extension, is there a way to vary the sample size (n from 50 to 1000, in increments of 50) and the number of independent variables (k=1 to k=100 in increments of 1) in the simulation? Best, J. ____________________________________________________ Prof. John Antonakis Associate Dean Faculty of Business and Economics University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 Faculty page: http://www.hec.unil.ch/people/jantonakis&cl=en Personal page: http://www.hec.unil.ch/jantonakis ____________________________________________________ On 07.08.2009 12:06, Martin Weiss wrote: > <> > > You could also -tokenize- the return from -indeplist- and have your -program- return the regressors one by one... > > > ************* > capt prog drop sim > > version 10.1 > > program define sim, rclass > drop _all > set obs 100 > gen y = invnorm(uniform()) > gen x1 = invnorm(uniform()) > gen x2 = invnorm(uniform()) > gen x3 = invnorm(uniform()) > gen x4 = invnorm(uniform()) > gen x5 = invnorm(uniform()) > stepwise, pr(.2): regress y x1-x5 > qui indeplist > tokenize "`r(X)'" > ret loc one="`1'" > ret loc two="`2'" > ret loc three="`3'" > ret loc four="`4'" > ret loc five="`5'" > end > > sim > > ret li > ************* > > > > HTH > Martin > > > -----Ursprüngliche Nachricht----- > Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von John Antonakis > Gesendet: Freitag, 7. August 2009 11:47 > An: statalist@hsphsun2.harvard.edu > Betreff: st: Simulating stepwise regression > > Hi: > > I would like to simulate the below. Note, I am no fan of stepwise--I > just want to demonstrate it evils > > However, I do not know > > 1. what to put in the place of "??"--that is, I want the program to > capture only the variables that were selected in the model as being > significant > > 2. how to simulate the r-square. > > 3. how to extend the simulation (a new program) such that I simulate > from n = 50 to n=1000 (in increments of 50), crossed with independent > variables ranging from x1 to x100. > > Regards, > John. > > Here is the program: > > set seed 123456 > > capture program drop sim > version 10.1 > program define sim, eclass > drop _all > > set obs 100 > > gen y = invnorm(uniform()) > gen x1 = invnorm(uniform()) > gen x2 = invnorm(uniform()) > gen x3 = invnorm(uniform()) > gen x4 = invnorm(uniform()) > gen x5 = invnorm(uniform()) > > stepwise, pr(.2): regress y x1-x5 > end > > simulate ??? , reps(20) seed (123) : sim, > > foreach v in ?? { > gen t_`v' = /* > */_b_`v'/_se_`v' > gen p_`v' =/* > */ 2*(1-normal(abs(t_`v'))) > } > > ____________________________________________________ > > Prof. John Antonakis > Associate Dean Faculty of Business and Economics > University of Lausanne > Internef #618 > CH-1015 Lausanne-Dorigny > Switzerland > > Tel ++41 (0)21 692-3438 > Fax ++41 (0)21 692-3305 > > Faculty page: > http://www.hec.unil.ch/people/jantonakis&cl=en > > Personal page: > http://www.hec.unil.ch/jantonakis > ____________________________________________________ > > > > * > * 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: Re: st: Panel data regression***From:*Andreas Hatzigeorgiou <anha@umich.edu>

**st: Simulating stepwise regression***From:*John Antonakis <john.antonakis@unil.ch>

**st: AW: Simulating stepwise regression***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**Re: st: AW: Simulating stepwise regression***From:*John Antonakis <john.antonakis@unil.ch>

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