Because of the complex design of A.C.E.’s postenumeration survey (weighted cases within samples of block clusters), many of the empirically correct enumeration rates and match rates used in Malec and Maple’s model are more variable than the nominal sample sizes would indicate. To account for the extra variability, Malec and Maples (2005) used a pseudo-likelihood approach with effective sample sizes estimated by the bootstrap approach.

In this approach, both logistic regression models (for match rate and correct enumeration rate) have the following generic form:

where βi is the fixed effect for ith poststratum membership, µk is a random effect for the kth local census office, and αik is model error. Furthermore,

where ce(i) is an index representing the collapsing of the poststrata into 11 or 8 cells, depending on whether the model is applied to the E-sample or the P-sample. Malec and Maples (2005) were able to estimate the large number of parameters in these models using Bayesian simulation.

This research suggests that inclusion of small-area effects could substantially improve coverage estimates. Several questions remain: how best to treat the complex sample design, how many random effects can be included and at what level of aggregation, the best way to estimate the model parameters, and how the model fit should be assessed. The panel is impressed with this high-caliber research that addresses an important issue in coverage modeling; further work in this area would be very valuable.

Mulry et al. (2005) examined the following anomalous results in A.C.E. More than 5 percent of incorporated places1 in 2000 had an estimated net overcount of greater than 5 percent, and 0.5 percent had a net overcount of greater than 10 percent. This result runs counter to findings from the 1980 and 1990 coverage measurement programs of the potential net overcoverage due to true erroneous enumerations and duplications. In contrast with 2000, only 0.1 percent of places had an estimated net undercount of greater then 5 percent, and nationally, the degree of overcoverage and undercoverage were of essentially the same magnitude. There is a concern that the lack of balance of designated erroneous enumerations and designated omissions may be due to the use of proxy status and the type of census return as poststratification variables for the E-sample but not for P-sample computations.

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