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Why would this matter as long as they got a good geographical sampling? "We used Facebook to quickly reach a large number of county residents and because it al

Why would this matter as long as they got a good geographical sampling? "We used Facebook to quickly reach a large number of county residents and because it allows for granular targeting by zip code and sociodemographic characteristics. We used a combination of two targeting strategies: ads aimed at a representative population of the county by zip code, and specially targeted ads to balance our sample for under-represented zip codes. In addition, we capped registrations from overrepresented areas." Update: Okay, "Other biases, such as bias favoring individuals in good health capable of attending our testing sites, or bias favoring those with prior COVID-like illnesses seeking antibody confirmation are also possible."

rhema 6y ago
If part of the value for participants was to know whether they had antibodies, then those that had gone through a flu (or covid) would be more likely to respond. This means that the overall sample likely includes more people who had COVID than a true random sampling would.
- tshadley 6y ago
  It looks like there's an argument to be made it could overcount or undercount depending on importance of each potential bias. "This study had several limitations. First, our sampling strategy selected for members of Santa Clara County with access to Facebook and a car to attend drive-through testing sites. This resulted in an overrepresentation of white women between the ages of 19 and 64, and an under-representation of Hispanic and Asian populations, relative to our community. Those imbalances were partly addressed by weighting our sample population by zip code, race, and sex to match the county. We did not account for age imbalance in our sample, and could not ascertain representativeness of SARS-CoV-2 antibodies in homeless populations. Other biases, such as bias favoring individuals in good health capable of attending our testing sites, or bias favoring those with prior COVID-like illnesses seeking antibody confirmation are also possible. The overall effect of such biases is hard to ascertain."

rhema 6y ago

If part of the value for participants was to know whether they had antibodies, then those that had gone through a flu (or covid) would be more likely to respond. This means that the overall sample likely includes more people who had COVID than a true random sampling would.

tshadley 6y ago
It looks like there's an argument to be made it could overcount or undercount depending on importance of each potential bias. "This study had several limitations. First, our sampling strategy selected for members of Santa Clara County with access to Facebook and a car to attend drive-through testing sites. This resulted in an overrepresentation of white women between the ages of 19 and 64, and an under-representation of Hispanic and Asian populations, relative to our community. Those imbalances were partly addressed by weighting our sample population by zip code, race, and sex to match the county. We did not account for age imbalance in our sample, and could not ascertain representativeness of SARS-CoV-2 antibodies in homeless populations. Other biases, such as bias favoring individuals in good health capable of attending our testing sites, or bias favoring those with prior COVID-like illnesses seeking antibody confirmation are also possible. The overall effect of such biases is hard to ascertain."