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?
2. The use of half-open intervals
3. Stratification based on list inclusion
What is random-digit dialing?
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What are somewhat looser RDD methods that combine the use of directories with random dialing?
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?
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?
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?
What are dual-frame designs?
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