By Jelke Bethlehem
1. The survey procedure -- 2. uncomplicated techniques -- three. Questionnaire layout -- four. unmarried sampling designs -- five. Composite sampling designs -- 6. Estimators -- 7. facts assortment -- eight. the standard of the consequences -- nine. The nonresponse challenge -- 10. Weighting adjustment -- eleven. on-line surveys -- 12. research and booklet -- thirteen. Statistical disclosure regulate
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Additional info for Applied survey methods : a statistical perspective
2) Absence of selective forces. No elements or groups of elements were favored in the selection process, either consciously or unconsciously. (3) Miniature of the population. The sample can be seen as a scale model of the population. The sample has the same characteristics as the population. The sample proportions are in all respects similar to population proportions. (4) Typical or ideal case(s). The sample consists of elements that are “typical” of the population. ” This meaning probably goes back to the idea of lhomme moyenne (average man) that was introduced by the Dutch/Belgian statistician Quetelet, (1835, 1846).
Such elements can never be selected in the sample. An example of undercoverage is the survey where the sample is selected from a population register. Illegal immigrants are part of the population, but they are never encountered in the sampling frame. Another example is an online survey, where respondents are selected via the Internet. In this case, there will be undercoverage due to people having no Internet access. Undercoverage can have serious consequences. If the elements outside the sampling frame systematically differ from the elements in the sampling frame, estimates of population parameters may be seriously biased.
In subsequent chapters, it will be shown that selecting samples with unequal probabilities can also be meaningful. Under speciﬁc conditions, this type of sampling can lead to even more accurate estimates of population characteristics. The remainder of this chapter limits itself to sampling with equal probabilities. 2 Randomizers Drawing an equal probability sample requires a selection procedure that indeed gives each element in the population the same probability of selection. Elements must be selected without prejudice.
Applied survey methods : a statistical perspective by Jelke Bethlehem