Case - Scientific Telephone Samples
Scientific Telephone Samples (STS), located in Santa Ana, California, specializes in selling sampling frames for marketing research.14 The STS sampling frame is based on a database of all working residential telephone exchanges in the United States. Thus, STS can draw from any part of the country-no matter how large or how small. The information is updated several times per year and cross-checked against area code and assigned exchange lists furnished by telephone companies. Exchange and/or working blocks designated for business or governmental telephones, mobile phones, and other commercial services are screened out.
STS can furnish almost any type of random-digit sample desired, including
• National samples (continental United States only, or with Alaska and Hawaii)
• Stratified national samples (by census region or division)
• Census region or division samples
• State samples
• Samples by MSA
• County samples
• Samples by zip code
• City samples by zip code
• Exchange samples generated from lists of three-digit exchanges
• Targeted random-digit dialing samples (including over 40 variables and special databases for high-income areas, Hispanics, African-Americans, and Asians)
STS offers two different methods for pulling working blocks. Either method can be used regardless of the geographic sampling unit (for example, state, county, zip). The two versions are Type A (unweighted) and Type B (weighted/efficient). Type A samples are pulled using a strict definition of randomness. They are called "unweighted" samples because each working block has an equal chance of being selected to generate a randomdigit number.
Completed interviews from a Type A sample that has been dialed to exhaustion should be highly representative of the population under study. Type B, or "efficient," samples are preweighted, so randomdigit dialing numbers are created from telephone working blocks in proportion to the number of estimated household listings in each working block. Working blocks that are more filled with numbers will be more prevalent in a sample. For example, a working block that had 50 known numbers in existence would have twice the probability of being included as one that had just 25 numbers.
Type B samples are most useful when a researcher is willing to overlook a strict definition of randomness in favor of slightly more calling efficiency because of fewer "disconnects." In theory, completed interviews from Type B samples may tend to overrepresent certain types of working blocks, but many researchers feel there is not much difference in representativeness.
Questions
1. Evaluate the geographic options offered by STS. Do they seem to cover all the bases?
2. Evaluate the STS method of random-digit dialing.