Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Joerg Luedicke <joerg.luedicke@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: tuples, stepwise and counting types of variables |

Date |
Tue, 14 Aug 2012 09:18:45 -0500 |

If you are only interested in a prediction model, why do you even care about parsimony? Why not just throwing in all of your predictor variables? J. On Mon, Aug 13, 2012 at 7:24 PM, Thomas Sohnesen <sohnesen@gmail.com> wrote: > Thanks Nick > > For this exercise i'm not interested in the coeffiicents or their > meaning, i'm looking to find a parsimonouce model for predictions. > Any advice on a better alternative than stepwise? Doing it manually > is not really an option as we will be running a lot of different > models. Further, though my data is organized in blocks i would like to > keep single variables if they are highly correlated with my dependent > variable. I believe SAS has an alernative in MAXR. Do you know if > stata has a similar alternativ? > > Finally, no matter which alternativ we end up using, i still have the > challange of counting number of variables from each block in the final > model. Any insights on that? > > thanks and best > > Thomas > > > On Mon, Aug 13, 2012 at 5:30 PM, Nick Cox <njcoxstata@gmail.com> wrote: >> I belong to a club which is dedicated to advising people against using >> -stepwise-. A -search- will find an FAQ on this question. >> >> I'd look at -nestreg- instead. >> >> Nick >> >> On Mon, Aug 13, 2012 at 10:18 PM, Thomas Sohnesen <sohnesen@gmail.com> wrote: >> >>> I have a number of "groups" of variables as examplified below. >>> >>> >>> local gr1 x1 x2 x3 x4 >>> >>> local gr2 x5 x6 x7 x8 >>> >>> local gr3 x9 x10 x11 x12 x13 x14 x15 >>> >>> local gr4 x16 x17 >>> >>> >>> >>> I run stepwise regressions for all the combinations of these groups >>> using tuples. >>> >>> tuples "`gr1'" "`gr2'" "`gr3'" "`gr4'" , display >>> >>> forval i = 1/`ntuples' { >>> >>> qui stepwise, pr(0.05): regress y `tuple`i'' >>> >>> } >>> >>> >>> >>> Now i would like to count how many variables from each group that >>> stayed in the step wise model. >>> >>> >>> >>> For instance in the stepwise regression of gr1 and gr2 (ei x1 x2 x3 >>> x4 x5 x6 x7 x8) only x3 x4 x5 was included in the regression. I >>> would then like an output along the lines of: >>> >>> Model Num_var_gr1 num_var_gr2 num_var_gr3 num_var_gr4 >>> >>> gr2 gr3 1 2 0 >>> 0 >>> >>> gr2 gr4 >>> >>> gr1 gr2 >>> >> * >> * 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**:**st: tuples, stepwise and counting types of variables***From:*Thomas Sohnesen <sohnesen@gmail.com>

**Re: st: tuples, stepwise and counting types of variables***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: tuples, stepwise and counting types of variables***From:*Thomas Sohnesen <sohnesen@gmail.com>

- Prev by Date:
**st: McNemer's Test with OR = 0** - Next by Date:
**Re: st: About Data transfermation** - Previous by thread:
**Re: st: tuples, stepwise and counting types of variables** - Next by thread:
**st: interaction expansion for corr or pwcorr** - Index(es):