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Participants suggested an alternative sampling frame that would resemble the target population more closely. This sample would include all known newspapers with housing advertisements circulating in the test site. With this method, researchers would lose a priori knowledge of the selection probability for a given advertisement. However, this limited knowledge may not be necessary since the true probabilities can be computed and weighted appropriately. This alternative sampling frame would yield unequal probabilities of selection, but participants did not view this as a major limitation.

Another alternative, raised by Tom Louis of the RAND Corporation, would be to abandon the sample survey goal in favor of an alternative unbiased selection procedure. The objective would be to select neighborhoods or communities in which advertising is prevalent without the goal of selecting a random sample. This method would ignore the sampling procedure and would not be concerned with sample survey weights or statistical comparisons within samples. Louis also noted that the reliance on advertisements produces selection bias since part of the market is missed (e.g., availability that is “advertised” through word of mouth). The researchers responded that pilot tests in the current study design include nonadvertisement sampling that begins to address this issue by identifying areas that are either protected (e.g., gated communities) or neglected (e.g., small communities that do not typically advertise available housing units in newspapers). Field reconnaissance in these areas provides researchers with available housing stock from which a secondary sample is drawn.

Participants discussed several ways to make the sampling frame more realistic. For example, one could look at the income and asset distribution of the minority population in individual metropolitan areas and sample housing units on the basis of that distribution. Urban Institute researchers pointed out that this sampling frame is quite different from one in which the sample of units is based on the distribution of where minorities currently live—an alternative approach offered during the discussion of auditing in underserved communities (see Chapter 6). The researchers expressed concern about this latter modification because it would institutionalize outcomes that may be the result of discrimination.

Participants were asked to discuss ways of making the sample more representative of the target populations, but in a neutral manner with respect to potential variants existing in the housing market. There was substantial agreement that this would be extremely difficult to do unless HUD were able to clarify the population to which it wants to generalize. The



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