Random digit dialing

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Random digit dialing (RDD) is a method for selecting people for involvement in telephone statistical surveys by generating telephone numbers at random. Random digit dialing has the advantage that it includes unlisted numbers that would be missed if the numbers were selected from a phone book. In populations where there is a high telephone-ownership rate, it can be a cost efficient way to get complete coverage of a geographic area.

RDD is widely used for statistical surveys, including election opinion polling [1] and selection of experimental control groups [2].

An important consideration in random digit dialing surveys is bias introduced by non-responders. Non-response bias can be a problem if responders differ from non-responders for the measured variables. For example, nonresponders may not have been contacted because they work multiple minimum-wage jobs. [3] Various techniques are used to reduce the non-response rate, such as multiple call attempts, monetary incentives, advance letters, and leaving messages on answering machines, because reducing the non-response rate may directly reduce non-response bias. [4] In addition, when trying to calculate total error estimates, response rate calculations can be imprecise because it can be difficult to determine whether certain telephone numbers are interviewable. [5] [6] Random digit dialing (RDD) is a method for selecting people for involvement in telephone statistical surveys by generating telephone numbers at random. Random digit dialing has the advantage that it includes unlisted numbers that would be missed if the numbers were selected from a phone book. In populations where there is a high telephone-ownership rate, it can be a cost efficient way to get complete coverage of a geographic area.

RDD is widely used for statistical surveys, including election opinion polling [7] and selection of experimental control groups [8].

An important consideration in random digit dialing surveys is bias introduced by non-responders. Non-response bias can be a problem if responders differ from non-responders for the measured variables. For example, nonresponders may not have been contacted because they work multiple minimum-wage jobs. [9] Various techniques are used to reduce the non-response rate, such as multiple call attempts, monetary incentives, advance letters, and leaving messages on answering machines, because reducing the non-response rate may directly reduce non-response bias. [10] In addition, when trying to calculate total error estimates, response rate calculations can be imprecise because it can be difficult to determine whether certain telephone numbers are interviewable. [11] [12]

When the desired coverage area matches up closely enough with country codes and area codes, random digits can be chosen within the desired area codes. In cases where the desired region doesn't match area codes (for instance, electoral districts), surveys must rely on telephone databases, and must rely on self-reported address information for unlisted numbers. Increasing use of mobile phones, number portability, and VoIP have begun to decrease the ability for RDD to target specific areas within a country and achieve complete coverage.