East Bay Jewish Community Study - Jewish Federation of the ...

Sampling Design
The survey employed three different types of sample, each with their own sampling method:
random-digit-dial (RDD) landline sample (n=620 completed interviews), listed cell phone sample
(n=100 completed interviews), and listed landline phone sample (n=100 completed interviews).
1) RDD Landline Sample: The representative landline sample employed an RDD procedure,
the gold standard in survey methodology, to obtain access to a representative sample of listed
and unlisted landline telephone numbers. The sample was ordered separately by the initial
regional definitions. The sample was pulled in replicates, a method for structuring sample that
allows for more a representative sample pull across a diverse population, initially using Type A,
a broader sample pull that accounts for the increasing size of sample exchanges. This method
is better at reaching a wider population area, but can lead to more disconnects and non-working
phone numbers. This type of replicate proved to be inefficient, so we switched to Type B, a
narrower sample pull that often results in a greater number of working phone numbers, after the
initial sample pull in order to better target productive telephone exchanges. Productivity of the
sample increased markedly. Due to the way California assigns telephone numbers and
exchanges, neither the switch from Type A to Type B nor the targeting of productive exchanges
should impact our ability to make accurate population estimates.
The RDD portion of the survey also employed an adaptive sampling procedure. We compiled
rough estimates of the Jewish population by county from a variety of sources, including previous
demographic studies of the East Bay Jewish population, and used these estimates to formulate
an initial target number of completes for each region and to pull the Type A sample. As we
began to collect data, we used the incoming data to re-calculate the incidence information and
formulate a more accurate number of completes. In all, we recalculated regional targets and
revised our incidence estimates four times during the fielding period to achieve the most
productive and efficient sampling plan possible.
Finally, we modified the sampling plan to slightly oversample regions with smaller Jewish
populations, in particular, Napa and Solano counties. Had we sampled these counties in a
purely representative way, we would have had too few interviews in these counties and been
unable to conduct a separate regional analysis. We oversampled these counties just enough to
obtain enough interviews to formulate population estimates in Napa and Solano without
impacting the overall representativeness of the sample as a whole. Following the survey, the
data were weighted so that the share of the Jewish population from each region reflected to the
expected, representative proportions of the Jewish population by each region and county. Thus
the final sampling plan sought to balance the need to obtain enough interviews in Napa and
Solano counties with our need to truly representative data for analysis.
The response rate for this portion of the sample was 2.4 percent overall (AAPOR response rate
4), meaning that 2.4 percent of numbers dialed completed the entire screening portion of the
survey. Approximately 6 percent of households reached using the RDD were Jewish
households, using the definition outlined above.
2) Listed Cell Phone Sample. Phone numbers for the cell phone sample were obtained from a
consumer list supplied by Info USA Corp, a reputable sample vendor. The total list contained
8,635 records for the greater East Bay region that had been deemed likely to be Jewish by the
vendor. This determination is made using consumer data, such as product purchases and
subscriptions, as well as membership lists, surname lists, and other sources. As a result, listed
cell phone sample tends to over-represent older Jews, more affiliated Jewish families, and those
with traditionally Jewish surnames. However, it provided the only feasible, cost-effective
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