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Random Start

The term random start has two separate meanings in survey research—one related to questionnaire item order and one related to sampling. This entry discusses both meanings.

Random Start in Questionnaire Construction

In terms of questionnaire item order, a random start means that a series of similar items (such as a set of agree-disagree questions) is administered in a way that the first question in the series that is asked of any one respondent is randomly chosen to “start” the series, and then the order of the subsequent questions is not randomized. For example, if Q23 through Q28 (six items in all) made up a set of attitude questions that use an agree-disagree response scale, by using a random start a researcher will have one sixth of the respondents asked Q23 first, one sixth asked Q24 first, one sixth Q25 first, and so on. All respondents are asked all the questions in the series, and each question follows its numerical predecessor, except when it is the first item asked in the series; for example, Q26 always follows Q25, except when Q26 is the first question asked (then Q25 is asked last as the random start order of the set would be Q26-Q27-Q28-Q23-Q24-Q25). The purpose of using a random start is to help control for possible item order effects, so that not all respondents will be asked the questions in the exact same order.

A random start set of questions differs from a random order set of questions in that the latter randomizes all questions within the set in all possible ways and then randomly assigns a respondent to one of the possible randomized orders. Random start questions are more readily analyzed and interpreted than random order questions, especially when there are more than a few questions in the set. Thus, for example, even with a set of 10 items using a random start deployment, a researcher with an overall sample size of 1,000 would have 100 respondents for each of the 10 random start orders in which the items would be asked. That would allow the researcher to investigate for order effects in how the random start series of questions were answered. In the case of a set of 10 items that were asked in a true random order, the permutations would be so great that the researcher could not investigate order effects with confidence unless the sample size were enormous (far greater than almost any survey would ever gather).

Random Start in Sampling

In terms of sampling, a random start refers to randomly selecting the first element in a systematic sampling procedure in order to avoid sampling error. Most forms of commonly used statistical analysis are based on the assumption that the data were selected using a procedure that allows for the calculation of a nonzero selection probability for each element in the sample frame. The least complex probability sampling procedure is simple random sampling, but this is not always an easy procedure to implement because it essentially requires that a separate random number be generated for each element to be selected for inclusion in the sample. Applied field work rarely presents the researcher with machine-readable lists of every eligible element of the population under study. Systematic sampling is often the preferred alternative.

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