Proceedings, First Workshop Panel to Review the 2000 Census (2001) / Chapter Skim
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process. I will talk about that in a little bit.
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We talked about this a little bit before. We started in the fall, where we listed all the addresses in rural areas.
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Right now we are on schedule. We are in a little bit of a lull right now.
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Before Howard begins, I would like to take the opportunity to say that I have spent a lot of time looking at the materials the Census Bureau has provided. I am delighted, really, and a little surprised, that we have received so much so quickly, and in such detailed form.
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listing] or that have more than two housing units listed by the census Master Address File [MAFi.
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sample design. We have too many clusters, because we selected them for a much larger number of housing units.
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Try to keep that separate from the block-sample reduction. This is where you go out and get blocks of 500 to 1000, 2000 housing units, for all sorts of reasons.
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lists more addresses than the census and blocks where the census lists more than the A.C.E. We have a Tot of information on the housing units in the block that we did not have initially.
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We cannot predict the synthetic bias, but we can perhaps scale it so that we make adequate allowance for it. Then we will estimate, in a very broad sense of the word, the mean squared error and variance for various proposals on the table.
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HOGAN: The post-stratification plays two roles, how we are going to form our dual-systems estimates, probabilities in terms of capture probabilities and erroneous enumeration probabilities. It is also how we carry down the estimates.
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As I said, we began by casting our net rather widely, including some things that are a little bit different than things we have tried before. I assume the panel members have their notebooks.
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Unlike tenure, which is an individual variable, this is looking at the community: Is it an area where a Tot of people rent or is it an isolated renter in an area where most neonle own their housing units? ~~ rural eve ^ Response rate is another environmental variable, really trying to tap into response to the census.
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We did not return there in planning census 2000. In the dress rehearsal, when we were forced to come up with state-bystate estimates, we were using raking to try to control some of the within-state variations.
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people and the census response to categorize the census, and you are going to use the census responses to carry down your estimates to the small area. If there was a systematic bias between how a variable was interpreted in the mailout/mailback census and the face-to-face interview in the A.C.E., or otherwise there was response and recall bias and variance, then the same person can go into two different cells, one depending on how he or she responded to the census and one depending on how he or she responded to the A.C.E.
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Age/sex is a little bit surprising. This is page 3 of the attachment.
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Its first real dry run happened to be the dress rehearsal. John earlier talked about how we are ctoing another operational test in Baltimore very soon to test our refinements.
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HOGAN: Yes. Through the evaluation studies, we checked the matching in the dress rehearsal.
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I assume you will use the census classification for race, for age, since you are going to apply whatever undercoverage factors you get to the census counts. Arn I correct on that?
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If you are getting bias because of the imputation, I think the problem is in the imputation method, not in the post-stratification.
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BRADBUR1! ;J: I would just make two generalizations to the category, because I think the household composition is a good example of that.
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Those two things should guide you a little bit, I think, in thinking about good candidates for stratification on this particular issue. It may be overridden by other things.
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I do not know. For instance, you could say, what do we do in terms of our estimates; how do the sex ratios compare to what we find with demographic analysis?
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On the other hand, if there was a big misclassification between whites living on reservations and American Indians living on reservations I do not think there was, but if there had been then we are moving people from an undercount of 3 percent to 18 percent. So it depends on which groups you are talking about.
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I think this is a little bit easier to interpret. These are the odds ratios for the various variables that went into the model.
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Or you could even take that and then say, what would happen if we added on another variable that looked interesting, at the cost of a few extra parameters? So you have more flexibility if you do a logistic regression model.
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DR. NORWOOD: There is a big difference, I might say, in being in the Census Bureau and having a discussion.
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Howard a little bit here. We sort of placed some constraints on Howard.
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It may be a little bit but it is a very minor increase in complexity. I think there is actually somewhat ot a gain In s~mpi~c~ty because you have a smaller number of post-strata at the end than 357, or something.
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Let's proceed} to what we are going to do next. The next step will be to select some post-stratification approaches and, for each post-stratification approach, simulate, based on 1990 data, a set of estimates for that post-stratum, and then map that back to 1990 51 post-strata groups, and in future research, map that back to cities or states or other geography, calculate the coverage factors you get from the various alternatives, try to predict the variance that you can expect at those levels, based on 1990 data, corrected for the new sample design and sample size for 2000, and also try to get an idea of the synthetic bias.
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It is essentially what is in Eric Schindler's paper, where you compare synthetic estimates or some moclel-based estimate to a direct estimate. Even if the direct estimates are noisy—you pick domains where the direct estimates may be noisy, but you can do the appropriate adding and subtracting of estimates of variance to get an estimate of mean squared error, and do that for a number of different types of domains, since this is a multi-objective problem.
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DR. HOGAN: The only other one we tried was a regional census center, the 13 areas that managed the census in 1990, to which the local offices reported.
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Given that you are dealing with a Hispanic renter, does it help to know it is in Boston or Indianapolis? I think there is something going on there and our logistic regression shows it which may help you with housing style.
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COHEN: This is probably something that almost everybody in the auclience already realizes, but for those who may be a little bit confused, the term being
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is to attack those kinds of systematic biases that we have never been able to address, regardless of what we have tried, specifically the differential undercount. That is very high on our priority list.
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In terms of this morning's topic, post-stratification, we are pretty well set in terms of using post-strata as opposed to a regression approach, probably something between 357 and 700, somewhere in that range—maybe a little bit more, but
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Working with our field division, it is clear that allocation to the states—we could go back and fudge it a little bit, but it is pretty well fixed. How within the state we allocate is pretty much open.
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Having applied that approach to the 1990 PES, what would the variance have been? But the same design in 2000 is quite different from the 1990 sample design.
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At some point you are going to have to say, "What do I know, perhaps from dress rehearsal, perhaps from other studies. nerhan.s from socinlo~v shout the.
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Your sex ratios would match demographic analysis and so forth. That is not reflected in this evaluation, the correlation bias aspect.
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This is our first pass-through in terms of getting beyond the logistic regression and trying out actual post-stratification alternatives. We are focusing on poststrata defined by age/sex, tenure, the urban size variable, region or regional census center, percent minority, mail return.
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These numbers are a little bit higher than if we had brought in the full model. So if some of these numbers look different, they are different.
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DR. BR017VN: Right, so what I really need is the results of the preceding analysis that gives me an estimate of mean squared error.
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This is one stage of the analysis. Because it is mapping back the alternatives to the 51 groups, we also have to map them back as state or city or other political geography.
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Again, this is just part of the process of looking at coverage factors themselves and they tell you what is going to happen. Looking at this I have been sort of staring at it for five minutes it looks as if there is not very much difference in the mociels, but there could be little differences if it is weighted in different ways.
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But also to the extent that, as you summed up, you got closer and closer to the domains that you are directly estimating, then you would expect the synthetic bias also to shrink. So both are going on.
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There is a whole series of things we are trying to do about the differential undercount. How do we think about that?
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We do have some tests we ran earlier in the decade, we have dress rehearsals, and we also have some studies on birth registration data, none of which directly answers how these people can be captured in the census. But it gives us data that people use to think through the problem.
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DR.NORWOOD:I am going to ask Howard to discuss briefly the sample design, and then move into, perhaps, the missing data. Then I am going to ask each of our visiting experts to make any comments that they want to share with us, and then other people on the panel.
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We also have the results of our new measures of size, which essentially can be broken into three categories here: the census and the A.C.E. basically agree on the number of housing units there; the census lists a lot more than the A.C.E.
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What we heard from the panel was, first, it is good to make sure that every state at least looks like it has an adequate sample, even if it is a synthetic estimate that you ultimately use. It is sort of protection if things are more geographic than your sample design had anticipated.
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MR. WAKSBERG: CPS state estimates were designed to provide not a synthetic estimate, but, presumably, good estimates.
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Once you have done 2 million, it is a shame not to squeeze all the information you can out of that. In addition to doing what you are talking about here, which is sort of using it selectively, you should be able to think in terms of some kind of a double sampling scheme, to help you in your estimate of missed housing units even something as simple as doing a computer matching check of addresses and using that as a basis of a double sampling-sample selection or estimation.
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But most of the areas that we samplecl as being pre(lominantly African American based on 1980 still were in 1990. When you get to some small groups, it is a little bit more problematic to control your sample size.
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In our dress rehearsal, we used a very simple ratio adjustment, controlling essentially on whether it went to follow-up or not. If a case went to follow-up, it obviously went to follow-up for a reason, which is often that it could not be easily matched.
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DR. HOGAN: We know in the resolved cases, for example, that very often a census miss creates a census erroneous enumeration, and vice versa.
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COMMENTS FROM PANEL MEMBERS AND GUESTS DR. ROBERT BELL: Let me make some comments, mainly about the sample design question.
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One idea that I think might be useful one of the things that was in one of these memoranda was a concern that in some states there were not very many minority blocks, when you looked at 50 percent or more minority. In some other states, if you took all the ones that were 50 percent minority, you sort of used up all the sample.
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You did not tell us how you would do it, but you did tell us you are worried about that. I want to emphasize again something that came up this morning, which is that the relation between the missing data question and the imputation question seems to me to be very important.
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When you talk about having both address files in hand to help decide block reduction, that means somebody is doing something that is integrating the two files or looking at them in comparison. I just want to make very certain that that does not spread outside of your office and in any way contaminate what goes on in the field.
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They said they were made by the Census Bureau to feel almost criminal if they even said hello to somebody who was on the other staff. They were so imbued with this fact that they had to keep completely separate.
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If our focus was more on just estimating the number of erroneous enumerations, we would probably do it a little bit differently. But our focus is on the net.
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Correlation bias arises because individuals within a post-stratum do not have the same probability of coverage in the census, and these probabilities are rather similar between the P-sample and the E-sample, or the census. There is information about correlation bias from demographic analysis, but only nationally.
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interview. There are some other details of this, but if you could do this, you would then have a means of seeing whether you could estimate correlation bias at the blockby-block level.
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There is probably enough information among 500 people to figure out where they really live. So if you can extend that idea a little bit further, to figure out what rules would have picked up some of the worst cases in 1990, you may save yourselves some real problems clown the road.
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You should explore more uses of demographic analysis than simply thinking in terms of sex ratios, black and white. I cannot be any more explicit because I do not know what I am talking about, but I just think it is something that should be considered.
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But it still seems to me that the key issue is, do you have systematic error in this let's say the household composition variables? I do not know.
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So I had a number of uncertainties about sample design, which we did not have time to go over.
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There is room for legitimate differences of opinion among experts about the choices that are being made, the decisions that have been made, that will be made, and a debate about whether some of the decisions were the best ones, or indeed even proper ones. So it is going to be a difficult program to explain when the census results are released, particularly if the results are considerably at odds, in some areas, with the census counts.
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You have done a Tot to improve that. But it seems to me and we have talked a little bit about this that places where there are big mismatches or errors between the initial adclress lists and updates, or various kinds of things, might be areas that you want to concentrate on.
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I think we have been concentrating a little bit too much on things we thought would reduce undercoverage. I think we ought to think about things that might increase gross errors and take that into consideration.
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in the neighborhood of 7.000 ~ , ~ , or Mu and growing every day, et cetera. You have begun to see a little bit in the press already, but you will see a lot more of it.
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largely according to our statistical design, which is 300,000 cases of the 750,000, which is not trying to make state estimates, which is a 12-month frame instead of a 9-month frame all kinds of properties of the A.C.E. are closer to what the Bureau would have wanted if you had asked us 8 or 9 years ago what the ideal way to do an A.C.E.
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I again want to compliment the staff. When you think about all the criticisms that a lot of people in the press and otherwise make of people who work for government agencies, it is quite clear that there are very few issues that have not been thought of by the people inside the Census Bureau and in which they have not done very high-quality work.
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