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Sample
Non-response rate
Even for censuses or random selections, the sample can be biased because, for example, some of the selected people might not fill in the questionnaire, or they might refuse to take part in an interview, or they might not be available, etc. The failure rate is often systematic, i.e. the people who do not participate in a study about a course may well be those who did not like the course. This might have a positive bias on the results. Itt is therefore necessary to examine who the non-responders are and the extent to which the failure (attrition) rate influences the results. If necessary, a further study should be conducted.
failure (attrition)
“The loss of subjects during the course of a study. This may be a threat to the (=>) validity of conclusions if participants of study and comparison/control groups drop out at different rates or for different reasons” (From: Nonprofit Good Practice Guide, Attrition) (=> Non-response rate)
Sample size
When determining the sample size (i.e. the number of elements in the sample), you should consider the following:
- The probability with which the value found in the sample corresponds to that of the population increases as the sample size increases.
- The more diverse the distribution of the variable of interest is within the population the larger the sample required.
- Reliable judgments of sample size can only be made if a hypothesis-testing investigation with a predetermined effect size is planned.
Further information about samples can be found at Wottawa & Thierau (1998, p. 114-143), Rossi, Lipsey & Freeman
(2004, p. 31-65), Weiss (1998, p. 87-96), Sapsford & Jupp (1996),
Gabler & Hoffmeyer-Zlotnik (1997), Bortz & Döring (2003).
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