OOPS-- I re-did the PUMS run to have the same age groups as the ACS standard tab. Not thinking clearly on a Friday afternoon. Elaine -----Original Message----- From: ctpp-news-bounces(a)chrispy.net [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Elaine.Murakami(a)dot.gov Sent: Friday, March 11, 2011 3:46 PM To: ctpp-news(a)chrispy.net Subject: RE: [CTPP] IPF macro? Here is the challenge! I do not know how to do IPF, but I know that many of you out there can do it! Attached are: ACS B08101 ; ACS B08006 for Maricopa County Arizona. You can ignore the MOE cells for this IPF challenge. Also attached is a 3-way tabulation using IPUMS for Maricopa County AZ. All are using 2009 ACS. You will note that carpool is not broken out, as the question is really in 2 parts (what mode, and then how many people), so this table could be re-done by creating a carpool variable, if you wanted. We have an archived webinar on using IPUMS, if you are interested in making your own tabs using ACS PUMS. http://ctpp.transportation.org/Pages/webinardirectory.aspx Elaine -----Original Message----- From: ctpp-news-bounces(a)chrispy.net [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Erlbaum, Nathan (DOT) Sent: Friday, March 11, 2011 11:42 AM To: ctpp-news(a)chrispy.net Subject: RE: [CTPP] 2010 Data Release Watch Noted below is a question and a response that appeared on the list serve earlier today and that suggests a solution method to creating data that almost exists but is needed. I am reposting this to the list serve, because I believe that this might be a worthwhile effort for someone who is adept and familiar with IPF to provide a valuable resources to the CTPP community in much the same way the ACS MOE spreadsheets have evolved to explain how to deal with this statistical concept in an easy to use way for the practitioner. Recently there was a post to the listserve by Jonnette Kreideweis about the Census Conference in California and the call for papers. There was also a recent post about the Planning Methods Conference. A spreadsheet that would answer the question posed is potentially a good basis for a paper. Further it helps share skills with the larger practitioner community based upon solutions and techniques that others have implemented. When presented and discussed on a listserve then many more people perhaps those who might never consider this as an option may now have a solution to the very same problem or may move on to adapt the method to other analysis areas. I want to encourage anyone who has the time to give it a try, maybe a student can use this to apply what they have learned, or a modeler can cannibalize something he/she has already used, many may benefit from you efforts. ---------------------------------------------------------- Nathan Erlbaum Associate Transportation Analyst Office of Policy, Planning & Performance New York State Department of Transportation 50 Wolf Road, 6th Floor Albany, New York 12232 (Tel) 518.457.2967 (Fax) 518.457.4944 (E-mail) nerlbaum(a)dot.state.ny.us (Web) www.nysdot.gov Marcus Wigan wrote: > ed > > a terribly simple question > > How best to do age group by gender by travel on the CTTP! > best > marc > Ed Christopher's response: Unfortunately, there is no clean way to get Age by Gender by Mode (Means of travel), that I know about, directly out of the current 3-year CTPP data product nor the Standard Census ACS products for that matter. However, there are some options that will get you close but they will take a little work. Option 1. In CTPP take table 12201 ( Age by Mode to work) and table 11203 (Age by Sex/gender)and run an IPF (Iterative Proportional Fitting-fratar) routine between the two tables to get what you want. At least I think it will work. Option 2. Do the same with standard ACS product tables B08006 (Sex by Mode) and B08101 (Mode by Age). If you go this route I think these tables may even exist in the 5-year ACS so you could do it at smaller than Places over 20K population geography. Option 3. Just make your table using the PUMS data but you would be limited to geographical areas of over 100K people. Over the years we has suggested that people use an IPF routine to make tables that might not exist in the various data products. I would be interested in hearing if anyone has actually done it. Have you?