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From |
Joerg Luedicke <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Looping over variables in more than one group |

Date |
Wed, 7 Mar 2012 08:00:52 -0800 |

You should probably rather think about what covariates make the most sense to include with respect to your theory and research question. Digging up variables to cook up good looking p-values and then interpreting these p-values in the usual way is a questionable endeavor, to say the least. However, if you are rather interested in something like a prediction model, and not in hypothesis testing, you could just use straight data mining techniques right away, for example boosted regression (-findit boost-). J. On Wed, Mar 7, 2012 at 7:12 AM, jaweria seth <[email protected]> wrote: > Thanks Nick, > I understand this would result in a large number of models.. > however, I wouldn't be combining variables of the same category/group, > as this would bring up the issue of multicollinearity. > for example, I know for sure I need to add one variable each from > groups 1 and 2. group 1 contains variables that measure the > size/production of a business, and I am wondering which of those > variables would be most significant in a multi-variate model. I am > looking at t-stats in the regression output: if even one of the > variables included is not significant at the 10%, that model gets > dropped..( and as im running the regressions manually, i find that the > majority of the combos are not significant). > > Does this make sense? If so, how can I implement it? > The way I am doing it right now: Holding one variable from group2 > constant and looping through group 1/size variables to find > significance. however, this gets tricky when I try to include a third > variable. > > > Thanks, > > On Wed, Mar 7, 2012 at 2:34 AM, Nick Cox <[email protected]> wrote: >> Before you even think of how to implement this, do the combinatorics >> of how many models this implies. >> >> So, for example, >> >> . di 30^4 >> 810000 >> >> . di 5^4 >> 625 >> >> Then bump up those numbers adding in the null choices, i.e. no >> variable from each group, as well. >> >> So you would need not only to do the looping but to ponder what it >> implies in terms of gathering results from thousands of models, >> finding the "best", whatever that means, including the implications >> for how you think about the resulting P-values, etc. >> >> Nick >> >> On Tue, Mar 6, 2012 at 10:01 PM, jaweria seth <[email protected]> wrote: >> >>> I would like to run regressions with up to 4 different variables. My >>> variables are separated into 4 groups with 5-30 variables in each >>> group. I would like to run regression combos of different variables to >>> find the best model: >>> How do I regress my y variable on 1 variable from group 1 and 1 from >>> group 2 and loop through different combos of each? >>> for ex: >>> regress Yvariable Group1 Group2 >>> >>> Then I would like to add a variable from group 3, and so on.. >> * >> * 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/

**Follow-Ups**:**Re: st: Looping over variables in more than one group***From:*jaweria seth <[email protected]>

**References**:**st: Looping over variables in more than one group***From:*jaweria seth <[email protected]>

**Re: st: Looping over variables in more than one group***From:*Nick Cox <[email protected]>

**Re: st: Looping over variables in more than one group***From:*jaweria seth <[email protected]>

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