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Framing the population - Problems with lists - Coping with omissions

Q: What are somewhat looser RDD methods that combine the use of directories with random dialing?

1. 'Add 1' : select a sample of numbers from the printed telephone directory and 'add 1' to the last diget of each selected number. 2. 'Replace two' : select a sample of numbers from the directory and replace the last two digits of each selected number with a two-digit random number.

8 important questions on Framing the population - Problems with lists - Coping with omissions

What is the most common way of coping with omissions and when makes this approach sense?

The most common way of coping with omissions is to ignore them and hope that the resulting bias is not serious. This approach usually makes sense if the list contains more than 90% of the population and does not omit important subgroups.

What are three methods to compensate for omissions?

1. Random-digit dialing
2. The use of half-open intervals
3. Stratification based on list inclusion

What is random-digit dialing?

The dialing of random numbers in working telephone exchanges so that unlisted numbers can be included.

What are somewhat looser RDD methods that combine the use of directories with random dialing?

1. "Add 1" : select a sample of numbers from the printed telephone directory and "add 1" to the last diget of each selected number.
2. "Replace two" : select a sample of numbers from the directory and replace the last two digits of each selected number with a two-digit random number.

Why are "add 1" and "replace two" biased in theory?

1. Because they miss new batches of numbers added since the directory was printed.
2. The favor banks of numbers that have a higher fraction of number listed in the directory.
In practie, though, the biases are not serious in most studies.

A study confirmed that sampling and data collection from the cell phone frame is feasible, but with what important caveats?

1. The cell sample had a significantly lower response rate than the landline sample, although the difference could be reduced with monetary incentives.
2. Call scheduling for cell phone users differ from that for the landline sample.

Another way to compensate for omission is the use of half-open intervals. What is this?

In this method the set of potential population elements is divided into subgroups, and one element in each subgroup is designated as "open". If the open element is drawn for the sample, then the full subgroup is searched for unlisted population members, and any unlisted elements discovered in this process are included in the sample.

What are dual-frame designs?

A more general way to compensate for omissions is to break the population elements into two groups, listed and unlisted. Listed elements are drawn from the list, and unlisted elements are pursued by other means.

The question on the page originate from the summary of the following study material:

Designing Surveys: A Guide to Decisions and Procedures | 9781412997348

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Framing the population - Problems with lists - Coping with omissions

8 important questions on Framing the population - Problems with lists - Coping with omissions

What is the most common way of coping with omissions and when makes this approach sense?

What are three methods to compensate for omissions?

What is random-digit dialing?

What are somewhat looser RDD methods that combine the use of directories with random dialing?

Why are "add 1" and "replace two" biased in theory?

A study confirmed that sampling and data collection from the cell phone frame is feasible, but with what important caveats?

Another way to compensate for omission is the use of half-open intervals. What is this?

What are dual-frame designs?

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