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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: conditional merging |

Date |
Wed, 7 Nov 2012 18:24:55 +0000 |

I will split this into two: 0. Interpolation. Carry-forward is crude but has the advantage that only legitimate values that occur can be carried forward. I decided this morning to write a nearest-neighbour interpolation program, which would have the same characteristic, except that the nearest neighbour could be later as well as before. The program would just be an analogue of -ipolate- and therefore not assume spacing in time, but would assume position in one dimension (not two). 1. Merging. I am not a merge-master. There should be others on this list who merge day in, day out and can give better advice. Nick On Wed, Nov 7, 2012 at 3:37 PM, Ben Hoen <bhoen@lbl.gov> wrote: > Thanks Nick. > > I am not sure there is a standard way that these "condition" values trend > over time across the whole dataset, and therefore interpolating them might > not be appropriate. Moreover, for each home, there might not be many data > points. Finally, the values that are allowable for condition are discreet > (non-continuous), and therefore would complicate a linear, cubic, cubic > spline process (though, of course that could be dealt with by using .=int(x) > ). Would the interpolation allow me to take into account all of these > characteristics? > > For, in part, this reason, I was hoping to find some way to execute a > "conditional merge" (again, my words). Additionally, the process of > learning how one might do it with this "condition" data, could be applied to > extracting other characteristic data that are also only present sporadically > across time (e.g., size of the home) but that also might periodically change > (e.g., the home might be added to). > > Is there a way to use if/then statements in a merge process? Nick Cox > Carry forward can be as little as one line of code: see > > FAQ . . . . . . . . . . . . . . . . . . . . . . . Replacing missing > values > . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. > Cox > 2/03 How can I replace missing values with previous or > following nonmissing values? > http://www.stata.com/support/faqs/data-management/replacing-missing-values/ > > I don't see that this is an imputation problem at all. It calls for > interpolation. Indeed, have you considered some kind of interpolation, > say linear, cubic, cubic spline? > > On Tue, Nov 6, 2012 at 7:33 PM, Ben Hoen <bhoen@lbl.gov> wrote: > >> I have two files sales.dta and condition.dta. sales.dta has two variables >> (home_id saleyear), and condition.dta has three variables (home_id >> inspection_year condition). The variable inspection_year can take the > vales >> of 2000-2011 for any home but for many homes only some years are present > (in >> many years the home was not inspected. Therefore a sample of the data > might >> look like: >> >> home_id inspection_year condition >> 50121 2002 4 >> 50121 2006 4 >> 50121 2011 3 >> 50681 2004 2 >> 50681 2010 3 >> 51040 2006 2 >> 51040 2010 2 >> 51040 2011 3 >> >> I would like to populate the sales.dta file with the condition of the > parcel >> in the inspection_year that is the closest to, but not following the >> sale_year. >> >> So, for example, the following dataset would result >> >> home_id sale_year condition >> 50121 2007 4 >> 50121 2011 3 >> 50681 2008 2 >> 51040 2003 . >> 51040 2010 3 >> >> I know I am not the first person to have this problem, but could not find >> threads on this. Maybe I am using the wrong search terms. Any help would >> be greatly appreciated. >> >> (As I wrote this I realized one not as elegant work-around would be to >> fill-in missing data for each missing year in the condition.dta file, >> potentially using the user-written "carryforward" or even imputing the > data >> using, e.g., mi impute, and then matching home_id sale_year to home_id >> inspection_year.) * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: conditional merging***From:*"Ben Hoen" <bhoen@lbl.gov>

**References**:**st: conditional merging***From:*"Ben Hoen" <bhoen@lbl.gov>

**Re: st: conditional merging***From:*Nick Cox <njcoxstata@gmail.com>

**RE: st: conditional merging***From:*"Ben Hoen" <bhoen@lbl.gov>

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