Weighting the BRFSS Data
When data are unweighted, each record counts the same as any other record. Unweighted data
analyses make the assumption that each record has an equal probability of being selected and that
noncoverage and nonresponse are equal among all segments of the population. When deviations from
these assumptions are large enough to affect the results from a data set, weighting each record
appropriately can help to adjust for assumption violations. In the BRFSS, such weighting serves as a
blanket adjustment for noncoverage and nonresponse and forces the total number of cases to equal
population estimates for each geographic region, which for the BRFSS sums to the state population.
Regardless of state sample design, use of the final weight in analysis is necessary if users are to make
generalizations from the sample to the population.
Following is a general description of the 2017 BRFSS weighting process. Where a factor does not apply,
processors set its value to one for calculation. In order to reduce bias due to unequal probability of
selection, design weighting is conducted. The BRFSS also uses iterative proportional fitting, or “raking”
to adjust for demographic differences between those persons who are sampled and the population that
they represent. The weighting methodology is therefore comprised of two sections: design weight and
raking.
Design weights are calculated using the weight of each geographic stratum (_STRWT), the number of
landline phones within a household (NUMPHON2), and the number of adults who use those phones
(NUMADULT). For cellphone respondents, both NUMPHON2 and NUMADULT are set to 1. The formula
for the design weight is:
Design Weight = _STRWT * (1/NUMPHON2) * NUMADULT
In 2017, the inclusion of cellular telephone respondents who also have landline telephones in their
residence and landline telephone respondents who also have a cellular telephone in their residence
required an adjustment to the design weights to account for the overlapping sample frames. From each
of the two sample frames, a compositing factor was calculated for the telephone dual sampling frame
users. BRFSS multiplied the design weight by the compositing factor to generate a composite weight for
the records in the overlapping sample frames as described in the section below. BRFSS then truncated
the design weight based on quartiles within geographic region, which processors used as the raking
input weight.
The stratum weight (_STRWT) accounts for differences in the probability of selection among strata
(subsets of area code/prefix combinations). It is the inverse of the sampling fraction of each stratum.
There is rarely a complete correspondence between strata, defined by subsets of area code/prefix
combinations, and regions, defined by the boundaries of government entities.
BRFSS calculates the stratum weight (_STRWT) using the following items:
• Number of available records (NRECSTR) and the number of records users select (NRECSEL)
within each geographic stratum and density stratum.