When the respondent sample size in a cell of the cross-classification of these two variables is too small, adjacent months are combined. Within each cell, the NIFM is calculated as the ratio of the sum of the weights after step 2 for responding and nonresponding CAPI housing units to the equivalent sum for only the responding CAPI housing units. No adjustments are made to the step 2 weights for non-CAPI, vacant, or ineligible units. No adjustment is made for over 75 percent of housing units, and only 5 percent of the NIFM adjustments are 1.10 or larger.
The next step is to calibrate the estimates based on the weights after step 3 to those produced using the NIFM weighting adjustments. The calibration is performed within each estimation area for the cell totals of the cross-classification of tenure (owned, rented, or temporarily occupied), tabulation month, and marital status of the householder (married and widowed or single). When the sample size in a cell is deemed too small, the two marital status cells are combined. Estimates of the cell totals are produced for each cell, and then the mode bias noninterview factor for a cell is computed as the ratio of the estimated cell total using the step 2 NIFM-adjusted weights to the corresponding estimated total using the step 3 adjusted weights. In the final step, the MBF factors are applied to the step 3 weights for all occupied housing units. As noted above, the MBF adjustments are generally small.
The effects of the compensation for nonresponding housing units using the combination of steps 3 and 4 are not obvious and need to be carefully assessed. For example, it is not clear that the NIFM weighting adjustments, which are confined to CAPI cases but drop the tract-level control, lead to less biased estimates for the cells in the cross-classification of the control variables, let alone estimates for other variables. Also, since the estimates of the cell totals for the control variables under the weights developed up to this point are equated to those using the NIFM-adjusted weights, their sampling errors are those of the latter estimates. These sampling errors are likely larger than those based on the NIF1 and NIF2 (step 3) adjustments alone, because the NIFM adjustments are applied only to CAPI cases and also because CAPI cases start with higher base weights because of the subsampling. Thus, the effect of the MBF step 4 adjustments, which derive from the calibration of the NIFM weights to the step 3 weights, on estimates of the control variables and on other ACS estimates needs examination.
Given the high response rates achieved in the ACS, the nonresponse adjustments have mostly a minor impact. However, for areas with lower response rates, the adjustments may be significant. Research to compare the current adjustments with other, more standard, adjustments is warranted. For example, in some estimation areas, a raking adjustment procedure applied to the marginal totals by census tract, building type, and month of data collection and confined to CAPI cases might be more effective.