14 Mar
2013
14 Mar
'13
1:56 p.m.
Warning! This may ramble so if you do not care about the issue delete.
Steve I am looking for specific references to the "limit of 3". I know
I have heard this many times and in fact tested it myself. Using data
from the Missouri State Data Center I got Tract data for the modes
people use to go work for my neighborhood Tract. With the Missouri data
they had published the total commuters calculated with a MOE along with
the total workers. I then went and pulled the 4 block groups for my
neighborhood from the census website. At the time the Missouri Data
Center did not have Block Group data published. I do not know if they
have them now, I did not check. While I could get the breakdown of the
modes for the BGs, the table did not have the total commuters as a
subtotal with a corresponding MOE. I figured I could just calculate my
own adding up the 5 modes and do the calculation. Before I went off to
do this the scientist in me took over and I tested the formula on the
tract data just to see if I could replicate the published MOE for the
total number of commuters. I could not do it. Fortunately, Liang Long
came to my rescue and suggested that I just take the Total number of
workers and subtract those who work at home (both of which have MOEs)
and try that. It worked! I could replicate the published MOE. What
this did was prove that as you more variables to the mix the formula for
calculating the MOE breaks down.
For what I was doing I was able to find a way of only working with two
variables but many times you can not.
When I presented this at a transportation census conference in October
of 2011 several users in the "power users session" confirmed that they
had heard that 3 was the most variables you wanted to use at a time. I
did find this on the census site that says "limit the number of variables"
http://www.census.gov/acs/www/Downloads/data_documentation/Statistical_Test…
A few days ago I talked with Elaine Murakami about this and she had the
perfect rule of thumb for me. Since the whole MOE thing is just an
approximation anyway "just take the largest MOE in the string of numbers
you are aggregating and use that". If you think about it, this does
make some mathematical and more importantly intuitive sense. I wish we
could get some statisticians to help out here. We need easy, quick to
use methods.
Steven Farber wrote:
I think I jumped the gun before when stating concerns
over exploding MOE's.
Going back to the New York State Data Center document, you'll notice that the MOE has
increased in absolute terms when summing over areas, but dropped in relative terms in
comparison to the sum.
So MOE has increased but the Coefficient of Variation has dropped. In other words, our
aggregated estimate is more precise than each of the smaller area estimates.
http://www.census.gov/acs/www/Downloads/handbooks/ACSResearch.pdf - Appendix 3 contains
all the calculations required.
Ed, do you recall where you saw that this type of calculation should be limited to 3
summands at a time?
Steven Farber, Ph.D
Assistant Professor
Department of Geography
University or Utah
http://stevenfarber.wordpress.com
-----Original Message-----
From: ctpp-news-bounces(a)chrispy.net [mailto:ctpp-news-bounces@chrispy.net] On Behalf Of
liang.long(a)dot.gov
Sent: March-12-13 10:18 AM
To: ctpp-news(a)chrispy.net
Subject: Re: [CTPP] Working with County flow data
I can see why Census doesn't recommend do more than three variables at a time. When
you add 17 counties together, you get a much bigger area with more households sampled. In
theory, you should get a smaller MOEs compared each individual county. But if you derive
MOEs from those 17 counties, you will get a much bigger MOEs, which is contradictory to
the theory.
________________________________________
From: ctpp-news-bounces(a)chrispy.net [ctpp-news-bounces(a)chrispy.net] on behalf of Ed
Christopher [edc(a)berwyned.com]
Sent: Tuesday, March 12, 2013 11:15 AM
To: ctpp-news(a)chrispy.net
Subject: Re: [CTPP] Working with County flow data
Thanks--I know the spread sheet allows you to recalculate MOEs for more than three
variables but I remember doing more than 3 a while back and I was getting some wild MOEs.
When I dug into it I found something in the Census compass reports that said not to do
more than three variables at a time. I was hoping that someone figured out a way around
this.
Ed C
On Mar 12, 2013, at 9:59 AM, "Hoctor Mulmat, Darlanne"
<Darlanne.Mulmat@sandag.org<mailto:Darlanne.Mulmat@sandag.org>> wrote:
The New York State Data Center developed a Statistical Calculations Menu that includes an
option for computing the margin of error for the sum of three or more estimates. See
attached.
Darlanne Hoctor Mulmat
Applied Research Division - Criminal Justice/Public Policy San Diego Association of
Governments
619-699-7326
From: ctpp-news-bounces@chrispy.net<mailto:ctpp-news-bounces@chrispy.net>
[mailto:ctpp-news-bounces@chrispy.net] On Behalf Of
Ed.Christopher@dot.gov<mailto:Ed.Christopher@dot.gov>
Sent: Tuesday, March 12, 2013 6:57 AM
To: ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
Subject: [CTPP] Working with County flow data
Has anyone come up with some easy ways for collapsing and grouping counties together
using last week's county flow data and recalculating new MOEs. I have so many counties
that I want to group together that I am looking for a quick way that can handle
"lots" of counties. Another issue I am struggling with is that we are always
told not to group more than three variables at a time or the formulas for calculating the
new MOE do not really work. This is particularly troublesome especially if I am trying to
group 17 counties together. What it comes down to is 9 different calculations given that
I can only group 3 counties at a time together. Anyone figure out any short cuts or ways
around this short of disregarding the MOEs altogether? Given all the clustering that I am
looking at using the "cheat" sheets I am used to, I will be recalculating MOEs
for weeks.
Ed Christopher
<StatisticalCalculationsMenu.xls>
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Ed Christopher
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