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From |
Nick Cox <[email protected]> |

To |
[email protected] |

Subject |
Re: st: reshaping data? |

Date |
Fri, 26 Oct 2012 15:54:21 +0100 |

I am getting closer, but it seems to me that there is still some arbitrariness here. If I am 789 then the others are 790 and 791 and should be P_1 P_2. But which should be which? I can't see a rationale here. Nick On Fri, Oct 26, 2012 at 2:35 PM, <[email protected]> wrote: > dear Nick, > each item is observed each week (for two years, so I have 106 observations > for each supermarket in my sample), and belongs to a family. The families > include from one up to 16 items (the number of items is not fixed for each > fam). What follows is an example of a family made up of three items > > > Code_item week Q P Code_family > 789 1 8 2 1 > 790 1 25 4 1 > 791 1 9 1.3 1 > > 789 2 12 2 1 > 790 2 2 3 1 > 791 2 20 1.2 1 > > > and so forth for 106 times (each supermarket) > I'd like to regress Q on P (and other ctrl vbls, that I omit for brevity) > and the prices of the other two items (substitute goods), in other words to > have a dataset like follows: > > Code_item week Q P Code_family P_1 P_2 > 789 1 8 2 1 4 1.3 > 790 1 25 4 1 2 1.3 > 791 1 9 1.3 1 2 4 > > 789 2 12 2 1 3 1.2 > 790 2 2 3 1 2 1.2 > 791 2 20 1.2 1 2 3 > > thanks for your patience... > > > > Quoting Nick Cox <[email protected]>: > >> Sorry, but this seems to imply as many predictors as observations, >> which isn't a good idea. >> >> Presumably you don't mean that, so you have tell us more about your >> data structure for this to be clear to me. >> >> Nick >> >> On Fri, Oct 26, 2012 at 12:31 PM, <[email protected]> wrote: >>> >>> dear Nick, >>> I'd like to estimate separate regressions, one for each family, hence the >>> number of predictors would be the same for each family >>> >>> hope this clarifies >>> best >>> M. >>> >>> >>> Quoting Nick Cox <[email protected]>: >>> >>>> In that case I really don't understand what you are seeking. See also >>>> Yuval's comments. >>>> >>>> I've never come across a model in which there are a different number >>>> of predictors for different observations, although I am always happy >>>> to be educated. >>>> >>>> It seems to me that >>>> >>>> 1. Either you are applying a standard model, in which case you can >>>> give literature references. >>>> >>>> 2. Or this is a new model, in which case you need to explain how it >>>> would be set-up and estimated. >>>> >>>> Note that it's easy to get variables such as the mean of the other >>>> prices in the same family. See >>>> >>>> FAQ . . Creating variables recording prop. of the other members of a >>>> group >>>> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. >>>> J. >>>> Cox >>>> 4/05 How do I create variables summarizing for each >>>> individual properties of the other members of a >>>> group? >>>> http://www.stata.com/support/faqs/data/members.html >>>> >>>> >>>> On Thu, Oct 25, 2012 at 3:39 PM, <[email protected]> wrote: >>>>> >>>>> >>>>> dear Nick, >>>>> thanks for your prompt reply. Unfortunately, the number of items is not >>>>> fixed >>>>> best regards >>>>> Maria >>>>> >>>>> >>>>> Quoting Nick Cox <[email protected]>: >>>>> >>>>>> This model formulation makes me feel a bit queasy, but I think what >>>>>> you want is something like this. >>>>>> >>>>>> Suppose for concreteness the number of items is fixed at 8. (I don't >>>>>> see how this will work if the number is not fixed.) So, "for any value >>>>>> of 8" >>>>>> >>>>>> sort code_family code_item >>>>>> forval i = 1/8 { >>>>>> by code_family : gen P`i' = P[`i'] >>>>>> } >>>>>> >>>>>> Note that, contrary to your title, there is no -reshape- here as you >>>>>> want your observations to remain observations; at least that's my >>>>>> understanding. >>>>>> >>>>>> Nick >>>>>> >>>>>> On Thu, Oct 25, 2012 at 3:08 PM, <[email protected]> wrote: >>>>>> >>>>>>> I have to estimate the equation >>>>>>> >>>>>>> Q1=a+b1P1+b2P2+...bnPn+e >>>>>>> >>>>>>> >>>>>>> Where Q1 is the quantity of item 1 sold by a supermarket during a >>>>>>> week >>>>>>> , >>>>>>> P1 >>>>>>> is the price of item 1 in that week, the other prices are those of >>>>>>> the >>>>>>> n >>>>>>> items belonging to the same family of items. My data set is organized >>>>>>> as >>>>>>> follows: >>>>>>> >>>>>>> >>>>>>> Code_item week Q P Code_family >>>>>>> 789 1 8 2 1 >>>>>>> 790 1 25 4 1 >>>>>>> 791 1 9 1.3 1 >>>>>>> >>>>>>> 792 1 12 2 1 >>>>>>> >>>>>>> 800 1 7 2 2 >>>>>>> 801 1 20 1.2 2 >>>>>>> 802 1 11 1.6 2 >>>>>>> >>>>>>> 803 1 12 2 2 >>>>>>> >>>>>>> And so forth for the other weeks and families... >>>>>>> >>>>>>> >>>>>>> For each item, how can I include in my regression the prices of the >>>>>>> other >>>>>>> (n-1) items of the same family, ignoring the prices of the items >>>>>>> belonging >>>>>>> to other families? >>>> >>>> >>>> * >>>> >>>> * 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/ >>>> >>> >>> >>> >>> ---------------------------------------------------------------- >>> This message was sent using IMP, the Internet Messaging Program. >>> >>> >>> >>> >>> >>> **** Riservatezza / Confidentiality **** >>> In ottemperanza al D.Lgs. n. 196 del 30/6/2003 in materia di protezione >>> dei >>> dati personali, le informazioni contenute in questo messaggio sono >>> strettamente riservate ed esclusivamente indirizzate al destinatario >>> indicato (oppure alla persona responsabile di rimetterlo al >>> destinatario). >>> Vogliate tener presente che qualsiasi uso, riproduzione o divulgazione di >>> questo messaggio e' vietato. Nel caso in cui aveste ricevuto questo >>> messaggio per errore, vogliate cortesemente avvertire il mittente e >>> distruggere il presente messaggio. >>> >>> * >>> * 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/ >> >> * >> * 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/ >> > > > > ---------------------------------------------------------------- > This message was sent using IMP, the Internet Messaging Program. > > > > > > **** Riservatezza / Confidentiality **** > In ottemperanza al D.Lgs. n. 196 del 30/6/2003 in materia di protezione dei > dati personali, le informazioni contenute in questo messaggio sono > strettamente riservate ed esclusivamente indirizzate al destinatario > indicato (oppure alla persona responsabile di rimetterlo al destinatario). > Vogliate tener presente che qualsiasi uso, riproduzione o divulgazione di > questo messaggio e' vietato. Nel caso in cui aveste ricevuto questo > messaggio per errore, vogliate cortesemente avvertire il mittente e > distruggere il presente messaggio. > > * > * 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/ * * 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/

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