Presented by: Khaleel S. Hussaini PhD Bureau Chief, Public Health Statistics Division of Public Health Preparedness Judy Bass Arizona’s BRFSS Coordinator June 26, 2012

What are we covering and what we are not? We are talking about BRFSS and changes in methods. What are the changes and why? Implications of the changes. We are not talking about questions and modules, today but will schedule a separate time and place. We will not discuss costs. We will not discuss time- lines for the next report.

So what are the changes? Any guesses! BRFSS weighting process

The Behavioral Risk Factor Surveillance Survey (BRFSS) was initiated by CDC in1984. It is the largest ongoing telephone survey in the World. Like all surveillance systems BRFSS has adapted to both technical and non-technical changes. Technical terms to remember: POPULATION VS. SAMPLE

Population inferences can be made...

...by selecting a representative sample from the population

SAMPLING STRATEGY IN BRFSS

Disproportionate stratified sample

National Center for Health Statistics Estimates of Cell Phone Only Households in the United States, Source: Blumberg SJ, Luke JV. Wireless substitution: Early release from the Nation Health Interview Survey, January2008 -June 2011 Available at: /wireless pdf. Accessed June 14, /wireless pdf

According to CDC Cell phone interviewees can now be better represented as the sample is: More likely to be younger; More renters than home owners; More likely to be Hispanic; More likely to be single; There are also differences in attitude and behaviors between cell phone only users and those with landline phones.

WEIGHTING PROCEDURES Why weight?

What is weighting?  Sampling weights are needed to correct for imperfections in the sample that might lead to bias. It can include the selection of units with unequal probabilities, non-coverage of the population, and non-response.  Data weights take the design weighting and incorporate characteristics of the population and the sample  Final Weights (_FINALWT) = Design Weight * some form of data weighting

IN THE PAST….  Post-stratification was used as a weighting method.  It was based on known demographics of the population.  For BRFSS Post-stratification included: Regions within states; Race/ Ethnicity (in detailed categories); Gender ; Age (in 7 categories)  Post-stratification forces the sum of the weighted frequencies to equal the population estimates for the region or state by race, age and gender.  Post stratification weights are applied to the responses, allowing for estimates of how groups of non-respondents would have answered survey questions. 

POST STRATIFICATION VS. RAKING  Beginning with the 2011 dataset, raking will succeed post stratification as the sole BRFSS statistical weighting method.  Allows for the incorporation of a now crucial variable – telephone source (landline or cell phone) into the BRFSS weighting methodology (called _LLCPWT)

WEIGHTING Iterative Proportional Fitting (Raking)

RAKING Gender by race/ethnicity Age by gender Age by race/ethnicity Renter/owner Education level Martial status Detailed race/ethnicity Regions within states Phone source Rather than adjusting weights to categories, IPF adjusts for each dimension separately in an iterative process. The process will continue up to 75 times, or until data converges to Census estimates.

Why Incorporate IPF Now?  Computer capacity has increased.  Cell phones are becoming larger percentage of the total number of calls.  Non-coverage with declining response rates makes weighting more important than ever.

HOW DOES IT IMPACT US?

CONCLUSION  Raked weights impact differently for different variables.  Trend data and comparison cannot be established prior to 2009 due to changes in weighting procedures.  In 2008, there was only landline data available and hence raked weights reflected only landline.  With introduction of cell phones raking methods incorporated both landline as well as cell phone weights called _LLCPWT.  Starting in 2011 CDC will weight data only using raking methods which implies establishing any trends is not feasible.