Statistics for Real-Life Sample Surveys: Non-Simple-Random by Sergey Dorofeev

By Sergey Dorofeev

Samples utilized in social and advertisement surveys, particularly of the final inhabitants, are typically much less random (often via layout) than many of us utilizing them comprehend. until it's understood, this 'non-randomness' can compromise the conclusions drawn from the information. This e-book introduces the demanding situations posed by way of less-than-perfect samples, giving history wisdom and functional tips in case you need to take care of them. It explains why samples are, and occasionally can be, non-random within the first position; find out how to verify the measure of non-randomness; whilst correction by way of weighting is suitable and the way to use it; and the way the statistical remedy of those samples needs to be tailored. prolonged info examples convey the concepts at paintings. this can be a ebook for training researchers. it's a reference for the equipment and formulae had to take care of normally encountered occasions and, chiefly, a resource of reasonable and implementable ideas.

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Extra info for Statistics for Real-Life Sample Surveys: Non-Simple-Random Samples and Weighted Data

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Clearly, the closer together they are the less time the fieldworker has to spend moving between them to move on to the next interview or to return to make call-backs on the hard-to-reach selections. Sometimes interviewers are provided with a single selected address (a starting address) and required to follow a set of rules for selecting addresses at which to interview (relative to the starting address) and respondents within households. This is the lowest-cost option but it has the disadvantage that the resulting interviews are concentrated in a very small area.

The probability will be inversely proportional to the number of eligible persons in the household. There are field procedures that can be used to overcome this and to equalise the probabilities of selection in such a situation. 14 selection with unequal probability sequence numbers. These procedures clearly remove the household size bias but they present operational difficulties. They assume that it is possible to obtain the necessary information from each selected household. Some households may be uncontactable or uncooperative and the number of eligible persons may not be otherwise ascertainable.

Almost invariably, however, they are attributes that can be readily determined before the initial contact is made, or at a very early point in the interview. In some cases quotas may be set deliberately to over-sample or under-sample certain categories of the population, for the same kinds of reasons already discussed for probability sampling. The targets may be set for the individual attributes independently (half men, half women, half 18–35, half older) with no requirement that any interaction between the attributes be controlled.

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