NAMCS Estimation Procedures

Statistics were derived by a multistage estimation procedure. The procedure produces essentially unbiased national estimates and has basically four components: 1) inflation by reciprocals of the probabilities of selection, 2) adjustment for nonresponse, 3) a ratio adjustment to fixed totals, and 4) weight smoothing. Each of these components is described briefly below.

1. Inflation of Reciprocals by Sampling Probabilities
Since the survey utilized a three-stage sample design, there were three probabilities:
a) the probability of selecting the PSU;
b) the probability of selecting a physician within the PSU; and
c) the probability of selecting a patient visit within the physician's practice.

The last probability was defined to be the exact number of office visits during the physician's specified reporting week divided by the number of Patient Record forms completed. All weekly estimates were inflated by a factor of 52 to derive annual estimates.

2. Adjustment for Nonresponse
Estimates from the NAMCS data were adjusted to account for sample physicians who did not participate in the study. This was done in such a manner as to minimize the impact of nonresponse on final estimates by imputing to nonresponding physicians the practice characteristics of similar responding physicians. For this purpose, similar physicians were judged to be physicians having the same specialty designation and practicing in the same PSU.

3. Ratio Adjustment
A postratio adjustment was made within each of the 15 physician specialty groups. The ratio adjustment is a multiplication factor which had as its numerator the number of physicians in the universe in each physician specialty group and as its denominator the estimated number of physicians in that particular specialty group. The numerator was based on figures obtained from the AMA-AOA master files, and the denominator was based on data from the sample.

4. Weight Smoothing
Each year there are a few sample physicians whose final visit weights are large relative to those for the rest of the sample. There is a concern that those few may adversely affect the ability of the resulting statistics to reflect the universe, especially if the sampled patient visits to some of those few physicians should be unusual relative to the universe. Extremes in final weights also increase the resulting variances. Extreme weights can be truncated, but this leads to an understatement of the total visit count. The technique of weight smoothing is used instead, because it preserves the total estimated visit count within each specialty by shifting the "excess" from visits with the largest weights to visits with smaller weights.

Excessively large visit weights were truncated, and a ratio adjustment was performed. The ratio adjustment is a multiplication factor that uses as its numerator the total visit count in each physician specialty group before the largest weights are truncated, and, as its denominator, the total visit count in the same specialty group after the largest weights are truncated. The ratio adjustment was made within each of the 15 physician specialty groups and yields the same estimated total visit count as the unsmoothed weights.